To terminate a processing activity before it finishes, typically because one of the following occurred: an invalid input, a system error, or a lack of resources.

Less specific in representation, or without a relation to a specific instance. Does not mean “more generalized.” See also generalization.

In data modeling, the redefinition of data entities, attributes, and relationships by removing details to broaden the applicability of data to a wider class of situations, often by implementing supertypes rather than subtypes.

In data services, the process of layering virtualization between data and its source. It redefines the data attributes or relationships by hiding details of the location, entities, and/or relationships of the information to broaden the applicability of data structures to a wider class of situations (i.e., implementing supertypes rather than subtypes, data access objects, data services, etc.).

The process of partitioning a model into smaller subparts for presentation. Used in data modeling to show related areas in a more readable scale.

The presentation of all or part of a model detail. Used in data modeling to show higher levels of entities and relationships to illustrate the basic subject area contents.

Generally, the ability to obtain or make use of something.

In data management, the operation of reading or writing information.

To obtain or retrieve.

The ability to readily obtain data when needed.

See fact table, accumulating snapshot.

Degree of correctness or conformity to a true value.

Level of incidence of error; accurate records are error free and can be used as a reliable source of information.

In data management, how closely a piece of data reflects its true, real-world value. Data accuracy is the first and most critical component of a data quality framework.

Complying with a standard, model, or rule.

Free from defect or error.

See data warehouse, active.

A machine learning approach where the algorithm selects the most informative data points to learn from.

A contribution to the performance of a function or process. An activity is at a lower level than a function or process, but at a higher level than a task or step. Inputs, activities, and outputs combine to form a process.

One of the DAMA-DMBOK Functional Framework Environmental Elements. Each function is composed of lower-level activities, which may be grouped into sub-activities, and then further decomposed into tasks and steps.

The role of a person or an external system or device that interacts with the system, business, or component under analysis.

In general, not cyclic; not composed of regular cycles.

A characteristic of a graph where there exists at most one path between any two nodes. See also connected.

A query constructed and executed to answer an immediate and unanticipated question or need, in contrast to a planned query. For example, a dynamic SQL SELECT statement against a relational database, constructed by a knowledge worker using an English-like or point-and-click interface of a desktop-resident business intelligence tool. The data returned may drive further analysis and reporting. Contrast with planned query.

Systems that change their behavior based on feedback.

See metadata, administrative.

The world’s first operational packet-switching network, developed by the US Department of Defense. Precursor to the internet, which evolved into the World Wide Web.

An input designed to fool a machine learning model into making incorrect predictions.

An analysis technique that relates occurrences of activities by individuals or groups. Market basket analysis is a type of affinity analysis.

See chart, affinity diagram.

An autonomous entity that perceives its environment and acts upon it to achieve goals.

Data resulting from processes that combine and summarize atomic data.

Generally, the process of gathering parts into a whole.

In data management, a process that transforms atomic data into aggregate-level information by using an aggregation function such as count, sum, average, standard deviation, etc.

An iterative project management framework that breaks projects down into several phases, commonly known as sprints.

A group of software development methodologies based on iterative and incremental development, where requirements and solutions evolve through collaboration between self-organizing, cross-functional teams. See Agile methodology.

The notification of an event, usually exceeding a predefined threshold.

A set of rules or steps that will result in a defined end from a defined start.

Generally, an alternative reference to a standard name or term.

In relational database management systems, a database object that indirectly references another database object; for example, an abbreviated table reference within an SQL query.

In a distributed environment, an object that refers to another object to avoid having to use the full location qualifier of the other object. This alias is not dropped if the object referred to is dropped.

The first version of something released to a formal testing team.

A primary key that is valid and acceptable, but is not the preferred primary key. See also key, alternate.

Uncertainty in meaning or reference, depending on the context or usage. An ambiguous reference may have multiple meanings in the absence of context or usage specifications.

In the United States, a large continuous demographic survey that is sent to residents on a monthly basis, rather than decennially. It contains more demographic questions than the old census long form and provides more up-to-date information than was previously collected.

A private not-for-profit organization that coordinates the development and use of voluntary consensus standards in the United States and represents the needs of US stakeholders in worldwide standardization forums. Formerly the American Standards Association, from which we get the American Standard Code for Information Interchange (ASCII).

A signal represented by an oscillating wave rather than digital pulses.

The process of systematically collecting, cleaning, transforming, describing, modeling, and interpreting data.

A person who performs analysis or is skilled in analysis. See also business analyst; business systems analyst; data analyst; systems analyst.

Software that packages business intelligence technology to support a specific knowledge-driven business process.

See data, analytical.

The system of criteria and standards within which data are analyzed.

Business intelligence procedures and techniques for exploration and analysis of data to discover and identify meaningful information and trends.

A software tool that can process and analyze large quantities of data to aid decision-making.

In the context of data, points in the data that are significantly different from the others and do not conform to expected patterns or norms. Anomalies can manifest as errors, inconsistencies, or unexpected patterns, often impacting data quality, analysis, and decision-making.

Data that originally contained personally identifiable information (PII) but has been processed to remove any indications that could positively identify an individual person.

The standard form of SQL concurrently defined by the American National Standards Institute (ANSI) and International Organization for Standardization (ISO) and first released in 1986. Provides a consistent, vendor-neutral framework for relational database management systems, ensuring interoperability across such platforms as MySQL, PostgreSQL, SQL Server, and Oracle.

A small Java program that can be embedded in an HTML page. Applets cannot access certain resources on local computers, such as files and serial devices. Applets are also prohibited from communication with most other computers across a network.

Relevance to the current subject.

Ability to be put to specific use.

In computing, software functions and services implemented together to support one or more related business processes.

See architecture, application portfolio.

See architecture, application component.

See architecture, system.

See architecture, application component.

See database administrator, application.

The process of building and maintaining software applications.

The IT organization responsible for application development. Synonymous with software development or software engineering.

See architecture, application portfolio.

A published standard format for communicating with applications.

In a three-tier application architecture, the middle tier of software (and possibly hardware) where business logic is performed.

A company offering network access to application programs and services for other parties. ASPs typically provide the applications, infrastructure, and technical support for a monthly service charge.

A programming technique where each module is independent: it has no dependency on, is unrelated to, and does not communicate with all other modules.

In graph theory, a connection between two nodes in a graph. Also known as an edge.

In mathematics, a curved line.

Generally, a person trained in the planning, design, and oversight of the construction of something, usually buildings.

In information technology, an experienced and skilled designer responsible for architecture supporting a broad scope of requirements over time, beyond the scope of a single project. The term implies a higher level of professional experience and expertise than an analyst, designer, modeler, or developer.

A way of thinking about and understanding architecture and the structures or systems requiring architecture.

Generally, the design of any complex object or system, including the implied architecture of abstract things such as music or mathematics, the apparent architecture of natural things such as geological formations or living things, or explicitly planned architecture of human-made things such as buildings, machines, organizations, processes, software, and databases.

In data management, the organized arrangement of components to optimize the function, performance, feasibility, cost, and/or aesthetics of an overall structure.

In common use, the art and discipline of designing buildings and structures, from the macro level of urban planning to the micro level of creating furniture and machine parts.

A set of standard programming structures, design patterns, formats, and protocols for how software applications should operate and communicate with each other.

A master blueprint for an organization’s existing and planned portfolio of software applications, how they support the organization’s processes, and how they interface with each other and with the organization’s databases.

The portion of an enterprise architecture that describes organizational goals, roles, reporting structures, and locations, but excluding the enterprise data architecture, process architecture, technology architecture, and application architecture.

The overall design and implementation of components of the business intelligence environment, including:

• the data warehouse, data marts, and staging area databases;
• the flow of data from operational sources and these databases;
• the selection and configuration of database management systems and database administration tools used for business intelligence;
• the selection and configuration of data integration products used to extract, cleanse, transform, and load data;
• the design patterns and standards for data integration programs;
• the selection and configuration of business intelligence software products that enable access, reporting, and analysis;
• the data schemas presented to business professionals for ad hoc query and analysis;
• the user interfaces for query, analysis, and reporting; and
• the administrative controls put in place to safeguard the data.

The future-state business process models of an enterprise, used in conjunction with a business data architecture to perform information value chain analysis. Part of an enterprise architecture.

A distributed technology approach where application software processing is divided by function. Servers perform shared functions such as processing business rules, managing communications, managing databases, or providing print services. Clients performs individual user functions – providing customized interfaces, performing screen to screen navigation, offering help functions, etc. Client and server software may reside on the same hardware platform, but each component is designed to be distributed across a networked environment for efficiency.

An architecture where only the original manufacturer can make add-ons and peripherals.

In common usage, the physical technology infrastructure supporting data management, including database servers, data replication tools, and middleware.

The method of design and construction of an integrated data resource that is business driven, based on real-world subjects as perceived by the organization, and implemented into appropriate operating environments.

Generally, an integrated collection of models and design approaches used to align information, processes, projects, and technology with the goals of the enterprise. These high-level design artifacts typically describe target views of the enterprise. Enterprise architecture may include:

• an enterprise data model,
• related data integration architecture,
• a business process model,
• an application portfolio architecture,
• an application component architecture,
• an application component architecture,
• an organizational business architecture, and
• the enterprise information value chain analysis that identifies the linkage and alignment across these perspectives, and to enterprise goals.

Other models and other forms of architecture may also be included within the enterprise architecture.

In the Zachman Framework for Information Systems Architecture, the enterprise architecture generally includes design artifacts identified in Rows 1 and 2 (conceptual views of data, process, locations, events, roles and goals), the value chain analysis describing the linkages between these perspectives, and high-level decisions about how to implement technology supporting these concepts in an integrated manner.

The analysis and design of the data stored by information systems, concentrating on entities, their attributes, and their relationships.

The integrated set of design artifacts defining how data (including the logical data model), applications (including the application portfolio architecture and data integration architecture), and technology (including portfolios of technology products and standards) will integrate to support the business architecture.

The design for integration of metadata across data dictionaries, directories, and repositories.

A form of architecture where the user interface layers, the application processing layers, and the data management layers are all logically separate parts which communicate through services. Also called n-tier architecture. See also architecture, three-tier.

The published specifications for a computer by a vendor, allowing other companies to create add-ons to enhance and customize the machine, and to make peripheral devices that work properly with it. In practice, it has been difficult to engage on a corporate basis due to the risk involved in a source that has multiple editors and has little to no assurance of quality when in use. Outsourcing the risk to a second party, who then uses the open source and accepts the liability for the code, is then the way to engage with open-source code.

The structural design of process systems, such as computers, businesses, or other complex systems.

Enterprise process architecture typically includes

• a functional decomposition,
• process flow diagrams, and
• value chain analysis linking processes to data (subject areas or entities), organizations, roles, goals, applications, and/or projects.

Part of a technology architecture, identifying selected vendor-specific software tools and services. Although not implied in the name, it may also include industry-wide standards and protocols.

A representation of a system, including a mapping of functionality onto hardware and software components, and the human interaction with these components. Includes applications, software components, interfaces, and projects.

The master plan for the information technology technical infrastructure depicted in diagrams and specifications of hardware and system software products, locations, configurations, standards and adopted protocols, along with linkages of computing platforms and/or servers to existing and planned applications and databases.

A structure for a database environment consisting of a presentation tier, an application tier, and a data tier. The presentation tier is seen and used by the programmers and other users of a DBMS, also called the user schema or external schema. Presentation tiers can overlap. The application tier is the combination of all the defined structures in the presentation tier for a given database, also called the logical tier, data access tier, or middle tier. There may be additional data in the application tier that is not in any presentation tier. The data tier is the database administrator’s view of the database, also called the internal schema. The data tier is the definition of the physical storage structure of a database.

See database, archival.

A copy of a database or documents preserved in a secondary, lower-cost storage location, for infrequent historical reference and/or recovery.

To move stored data (structured or unstructured) to a secondary, less readily accessed location, at lower storage costs, for historical reference and/or recovery.

See chart, area cartogram.

See chart, area.

The number of object roles that a single predicate (relationship type) can have in its diagram representation. See also n-ary.

A grouping of similar items of the same storage type in a sequential pattern and referenced by a sequential index value. See also matrix.

A tangible output from an activity or task. For example, a logical data model, a requirement document, or a project plan.

Software that performs a function previously ascribed only to human beings. It can encompass such things as natural language processing, simple automated tasks, and complex problem-solving.

A computational model inspired by the human brain, used in machine learning.

A form of artificial intelligence (AI) that surpasses human intelligence in all aspects, including creativity and problem-solving. ASI represents intelligence far beyond human capabilities, such as autonomous self-improvement and the execution of any intellectual task more effectively than humans.

A common code used in transmitting information over networks, using 7 or 8 data bits, a parity bit, and a stop bit. See also EBCDIC (Extended Binary Coded Decimal Interchange Code).

Generally, something that has value or produces benefit.

In accounting, something of value on a balance sheet.

Describes how an asset or a service will perform in objective and measurable terms. The measurement is sometimes as simple as assigning a number. An example would be a range of 1 to 5, where 1 = poor and 5 = excellent.

Nonphysical asset, such as accounts receivable.

Physical asset, such as equipment.

To determine relationships between entities, including characteristics of the relationship: dependent or not (optional, orphan), exclusive (at most one) or not (multiple). See also relationship.

See relationship.

In statistics, any relationship between measured quantities that shows a statistic dependency.

In object-oriented programming, a relationship between object classes that enables an object instance to perform an action on another’s behalf.

The largest and oldest international scientific and educational computer society.

See relationship rule analysis.

See data entity, associative.

A style of communication in which the initiator does not wait for a reply. Opposite of synchronous.

Data replication where the target database is updated as soon as possible after updates occur to the source database, but not as part of a single integrated transaction. Failure to update the target has no impact on the source database. Sometimes referred to as near-real-time replication.

Data at the lowest chosen level of detail (granularity). The level of detail chosen depends on the information requirements of the enterprise. For example, address could be one atomic item, or address could be split into further composite items, such as house identifier and city. Opposite of aggregate data.

Non-aggregated observations, or measurements of characteristics of individual units, which cannot be further decomposed and retain any useful meaning.

Standard properties of relational databases.

A mechanism in neural networks that focuses on specific parts of the input data when making predictions.

A specific characteristic or property of a data entity that helps to define its nature and behavior within a dataset. In the context of data analysis and data science, attributes are crucial as they provide the necessary information to understand and manipulate data effectively.

See class, attribute.

See generalization, attribute.

See relationship, attributed.

See data entity, dependent.

A formal and official verification of validity, accuracy, and conformance to requirements, regulations, standards, and/or guidelines.

Data maintained to trace activity, such as a transaction log, for purposes of recovery or audit.

The process of adding to something to make it more or greater than the original.

In logic, a relationship where if X leads to Y, then XZ will lead to YZ.

A technology that superimposes a computer-generated image, sound, or other sensory enhancement over a user’s view of the real world.

In data security, the process of verifying whether a person or software agent requesting a resource has the authority or permission to access that resource.

In data quality, the process of verifying data as complying with what the data represents.

A source of data or information that is recognized by members of a community of interest (COI) to be valid or trusted because its provenance is considered highly reliable or accurate. During the life cycle process, the authoritative source (or system of use in which it is housed) can evolve according to use. Subject matter experts validate that the data is authoritative, and data management assures that data from the authoritative source is provided to users, and that it is current.

In data security, the granting of authority allowing a person, group, or software agent to access a resource.

In data security, a request to grant authority to a person, group, or software agent to access data for which the data consumer does not have access privileges.

See rule, authorization.

A method of automatically identifying and collecting data on items and then storing the data in a computer system. For example, a scanner might collect data about a product via an RFID chip.

The act of replacing control of a manual process with computer or electronic controls.

The percentage of time a system or data resource is accessible or expected to be accessible for productive work.

A figure that shows data using network or relational models. Named after Charles Bachman. Also called a data structure diagram.

To take a copy of a system to ensure its continued availability in the event of a hardware or software failure requiring recovery of the database to restore the data.

backup: The copy of the system information and data used for recoverability.

In computer architecture, the server-side part of a system that handles logic, data, and services behind the user interface.

In data warehousing, the 80 percent data management activities of enterprise data warehousing, such as data profiling, data modeling, and extract-transform-load processing.)

An Agile term for a list of desired user requirements, some of which may be a wish list. It identifies which features to implement first.

An AI core algorithm in training neural networks, where the error is propagated backward to adjust weights.

A backup snapshot taken while the system is offline.

A backup snapshot taken while the system is online.

Able to accept input from older or earlier versions of a device or software.

Operational on older technology, even if limited in functionality.

See recovery, backward.

A strategic performance-management tool consisting of a semi-standard structured report, supported by proven design methods and automation tools, that can be used by managers to keep track of the execution of activities by staff within their control and monitor the consequences arising from these actions. It provides a comprehensive, top-down view of organizational performance measurements with a strong focus on vision and strategy, based on concepts developed by Robert Kaplan and David Norton.

Criteria used to evaluate the qualification of companies for the Malcolm Baldrige National Quality Award; leading management practices used to measure organizational performance in seven categories: Leadership; Strategy; Customers; Measurement, Analysis, and Knowledge Management; Workforce; Operations; and Results.

The rate of transfer of data over a specific channel. See also capacity.

See chart, bar.

See data modeling notation, Barker.

In data warehousing, the normalized data structures maintained in a data warehouse, in contrast to the denormalized dependent data mart tables sourced from the base tables.

Outside of data warehousing, a table for an entity that is not dependent on any other entity in the database.

The unit used as the basis of an index number, or to which a constant series refers. For example: base period, base weight, base currency.

International banking supervision standards designed to ensure the liquidity of financial institutions doing business in European Union countries.

A method of processing high volumes of data where a group (or batch) of data is collected over a period of time and then processed together.

What something does at any point in time. The execution or carrying out of a process constitutes behavior. Behavior is something that happens, as opposed to something that is. Opposite of state.

Confidence in inherent truthfulness.

A statistical frequency distribution pattern that is shaped like a bell (narrow at ends, wide in the middle of the range). See also normal distribution.

A point of reference for measurement, comparison, and evaluation. A benchmark can be a standard of excellence or a point-in-time snapshot measurement for comparison with other benchmarks. A benchmark may be an internal or external measurement.

To analyze and compare an organization’s processes (an internal benchmark) against the performance of another organization or an industry standard (an external benchmark).

The process of comparing the performance of artificial intelligence models using standard datasets and evaluation metrics.

A technique, method, process, discipline, incentive, or reward generally considered more effective at delivering a particular outcome than other means.

A release of software to a limited population, under controlled conditions, to test for functionality completeness and execution correctness.

See test, beta.

Generally, a distortion of something to support a particular view.

In data analysis, a distortion of data or information that affects its interpretation, or a distortion of interpretation that supports a particular view.

In machine learning, a model’s error due to incorrect assumptions in the learning algorithm.

A distortion of fact interpretation based on sole use of data provided by or pre-selected by the sponsor of the research, which may be skewed toward a certain result, rather than being completely objective.

A distortion of fact interpretation due to non-random selection of sample contents.

A distortion of fact interpretation based on sole use of data that supports the desired outcome, rather than a complete dataset.

A distortion of fact interpretation by only using the results that support the desired outcome, and ignoring or not displaying the other results.

A naming convention for binary relationships where the relationship is described twice, in sentences, once with one entity named as the subject and the other entity as the object of the sentence, and again with the first entity as object and the second as subject.

Data volumes that are exceptionally large, normally greater than 100 terabytes and more commonly in the petabyte and exabyte range. Big data is used in data warehousing and analytic solutions where the volume of data poses specific challenges unique to very large volumes of data, including data loading, data modeling, data cleansing, and analytics.

Generally, an exchange of something between a sending organization and a receiving organization in which all aspects of the exchange process are agreed between counterparties.

In data management, an exchange of data and/or metadata between a sending organization and a receiving organization in which all aspects of the exchange process are agreed between counterparties, including the mechanism for exchange of data and metadata, the formats, the frequency or schedule, and the mode used for communications regarding the exchange.

The information and relationships that document the entire lifecycle of a product. Includes the associated product information (administrative, programmatic, technical, and financial) and its location.

A list of raw materials, down to the atomic level necessary to create a final item.

Consisting of two components or values.

The format of a compiled and linked program that is ready to execute on a specified system.

A unit of measurement for data based on the binary number system using zero and one. (From binary + digit.)

See relationship, binary.

A subset of personally identifiable data consisting of a person’s physical or physiological attributes, such as a retinal scan, fingerprint, or DNA.

See index, bitmap.

The amount of bits transferred over a conduit or connection in one second.

See index, block.

A decentralized, tamper-resistant digital ledger of all transactions across a distributed network, which can be used to record transactions across many computers so that any involved record cannot be altered without the alteration of all subsequent blocks.

The situation in which one process locks a resource that another resource needs. The second resource is “blocked.”

A type of website containing regular entries of commentary, notes, or links to graphics or video. Short for “web log.”

The sum of all professional knowledge in a given field, or what is generally accepted to be true.

A body-of-knowledge document available from the International Institute of Business Analysis.

A body-of-knowledge document created by the Association of Business Process Management Professionals International.

A body-of-knowledge document created by the business technology architects’ association Iasa Global (formerly International Association of Software Architects).

A project undertaken by the Canadian Information Processing Society to outline the knowledge required of a Canadian Information Technology Professional.

A guide to knowledge about data management published by DAMA International.

An archival body-of-knowledge document created by the International Association of Software Architects. Replaced by Iasa Global’s Business Technology Architecture Body of Knowledge (BTABoK).

Published by the International Information System Security Certification Consortium (ISC2). Contains the information tested to achieve the Certified Information Systems Security Professional designation.

Developed by Carnegie Mellon University, a body of knowledge on personal software process and team software process.

An acronym and registered trademark for the Guide to the Project Management Body of Knowledge, a publication of the nonprofit Project Management Institute (PMI) and an internationally recognized standard (IEEE Std 1490-2003) defining the fundamental vocabulary of project management and identifying generally accepted project management practices.

The Guide to the Software Engineering Body of Knowledge, a book published by the Institute of Electrical and Electronics Engineers (IEEE) Computer Society.

A marker used to save a place in a book or dataset, or an internet address.

Relating to or of an algorithm or calculation that results in only a True or False result. Named for George Boole.

Logical operators that combine propositions to evaluate to only a True or False result. Includes and, or, if–then, except, and not.

A search method using Boolean operators (and, or, not) to focus the search.

Also called Boston box. See chart, portfolio.

Short for robot. A computer program that runs on the internet and performs automated tasks for other users or programs. Bots can imitate human behavior, but they are faster and more accurate than humans at performing repetitive tasks. Some bots are designed with malicious intent and can have a negative impact on websites or applications.

A malicious bot. There are several kinds of botnets, including scam bots that harvest email addresses; website scrapers that grab content from websites and use it without permission; and spy bots that collect data about users without their permission.

See chart, box plot.

See chart, box plot.

See normal form, Boyce-Codd.

Standards for defining process flows using web services.

Standards for defining process flows controlled by web services.

In databases, a software function that prevents users from querying a database once transaction loads reach a certain level.

See table, bridge.

See index, b-tree.

See chart, bubble.

A software mechanism to move large data files that uses compression, blocking, and buffering to optimize transfer times.

See chart, bullet.

In data warehousing, a tabular representation of the intersection of shared dimension tables with data subject areas, data processes, data facts, data marts, etc.

Generally, any purposeful activity.

Specifically, a commercial or industrial enterprise. Commercial activity engaged in as a means of livelihood.

A set of methods or procedures that may be executed in the form of transactions relative to a business. See also activity; business process.

The ability to automatically monitor events in an executing business process through immediate notification, thanks to a sophisticated technical infrastructure.

The study of business processes, practices, and business systems requirements.

The application of information to better understand business opportunities and challenges. See also business intelligence (BI).

See Body of Knowledge, Business Analysis.

Generally, a knowledge worker responsible for interpreting data, performing calculations, and distributing reports to other knowledge workers.

In data management, a professional responsible for understanding the business processes and the information needs of an organization, serving as a liaison between IT and business units, and acting as a facilitator of organizational and cultural change. See also business systems analyst; systems analyst.

Metadata that includes data definitions, report definitions, users, usage statistics, and performance statistics.

See architecture, business.

A structured format for organizing the reasons, benefits, and estimated costs for initiating a project or program.

The degree of uninterrupted stability of an organization’s systems and operations in spite of potentially disruptive events.

Data about people, places, things, rules, events, or concepts used to operate and manage any enterprise (not just commercial enterprises). Used to identify data that is not considered to be metadata.

A knowledge worker, business leader, and recognized subject matter expert assigned accountability for the data specifications and data quality of specifically assigned business entities, subject areas, or databases, but with less responsibility for data governance than a coordinating data steward or an executive data steward.

See entity, business.

Data created while operational processes are in progress. Examples include customer orders, cash withdrawals, and supplier invoices. Also called transactional business data.

Connects data governance activity with business needs. Also called data governance strategy map.

A course studying design, import, and manipulation of text, graphics, audio, and video used in presentation management and publishing systems.

An organization’s continuously increasing, constantly changing need for current, accurate, integrated information, often on short notice or very short notice, to support its business activities. It is a very dynamic demand for information to support the business that constantly changes.

A set of concepts, methods, and processes to improve business decision-making using any information, from multiple sources, that could affect the business, and applying experiences and assumptions to deliver accurate perspectives of business dynamics.

Data that helps a data warehouse administrator manage a data warehouse, such as user profiles and data access history.

An IT professional specializing in assisting and supporting business professionals in becoming more self-sufficient in the use of query, reporting, and analysis procedures and tools. A business intelligence (BI) analyst trains knowledge workers, assists them in solving more complex analytical and reporting problems, and provides second-level support for user problems with BI data and tools, and may serve as the administrator for the BI environment.

An IT professional with overall responsibility for the business intelligence environment, its architecture, and the effectiveness of knowledge workers engaged in business intelligence (BI). A lead BI analyst. May also be the data warehouse architect, or these responsibilities may be distinct.

See architecture, business intelligence.

See architecture, business intelligence.

An IT professional software developer who specializes in report writing and/or the development of analytic applications.

The hardware, software, and organizational support for business intelligence activity that enables knowledge workers to access, analyze, and manipulate data. It generally includes the business intelligence software, user interfaces, associated infrastructure hardware and software, data mart databases, and multidimensional data cubes. It may also include data warehouses and the data integration programs that provide data for business intelligence.

The infrastructure of selected enabling tools and technologies necessary for the development and deployment of business intelligence applications.

An application service provider providing data warehousing and business intelligence capabilities as outsourced services hosted off-site. A BISP ties into source information systems and databases behind a corporation’s firewall, providing traditional data warehouse and analytic application capabilities to internal knowledge workers and external customers. Often used to extend business intelligence functions into e-commerce.

The creation, publishing, and sharing of custom business analytics reports and dashboards by end users of cloud technologies.

Technology and products (tools) used by knowledge workers to access data, analyze, and share information; understand business performance; and improve decision-making. Includes query and reporting tools, online analytical processing (OLAP) technologies, statistical analysis tools, data mining tools, scenario modeling tools, planning and budgeting tools, advanced analytic applications, dashboards and scorecards for performance monitoring, and enterprise reporting tools.

The training and assistance available to business professionals in use of business intelligence tools and techniques and the valid interpretation of BI data. Typically, a help desk provides Level 1 support, with BI analysts providing Level 2 support.

See key, business.

See metadata, business.

A current or future-state representation of some aspect of an enterprise, typically from a process, data, geographic, event, organizational, or financial perspective.

A container for application data, such as a customer or an invoice. Data is exchanged between components by business objects.

An umbrella term for the methods, metrics, processes, and systems used to monitor and manage the performance of any enterprise.

The use of techniques and tools to measure performance against specific key performance indicators, often coupled with comparative information from industry sources. Dashboards support business performance measurement. The Balanced Scorecard (BSC) is a specialized form of business performance measurement.

The use of techniques and tools to understand the factors affecting business performance and to explore “what if” scenarios to help consider the implications of alternative courses of action. See also scenario modeling.

A collection of related and organized functions, activities, procedures, steps, or tasks that follow a defined sequence to produce a product or service addressing a particular business requirement or objective.

Activities that may involve multiple stakeholders, including employees, technology, and tools, and are designed to ensure efficiency, consistency, and measurable outcomes.

See architecture, business process.

The design, monitoring, and control of complex interactions between people, applications, and technologies designed to create customer value.

A model that defines maturity levels for business processing from Initial, through Managed, Standardized, and Predictable, to Innovating. Developed by the Object Management Group.

A model of the functions, activities, and procedures performed in any organization. It may consist of:

• A context diagram showing the relationship of the overall process to those outside the model’s scope, along with the inputs to and outputs from the overall process;
• One or more functional decomposition diagrams showing how the overall process is made up of contributing processes at lower levels (a “vertical view”);
• One or more process flow diagrams showing how the outputs of one process serve as the inputs to other process (a “horizontal view”). The process flow may be cross-functional or within a single function;
• One or more business process model diagrams, each depicting the inputs, outputs, start and end events, component activities, roles, and metrics of a single process;
• The business definition of each process; and
• The value chain analysis of the process, identifying relationships to data, organizations, roles, and systems.

A stylized approach to graphically documenting the definition, objectives, start and end events, inputs, outputs, component activities, roles, and metrics of a single process. Sometimes referred to as a context diagram, but a BPM diagram includes more information than a traditional context diagram.

The standard for business processes diagrams. It is intended to be used directly by the stakeholders who design, manage, and realize business processes, but at the same time be precise enough to allow BPMN diagrams to be translated into software process components. Maintained by the Object Management Group.

A form of outsourcing that involves transferring responsibilities for entire specific business functions or processes to a third-party provider.

The process of analyzing and radically transforming existing business activities, eliminating or minimizing costs and maximizing value in order to achieve breakthrough levels of performance improvement.

See requirement, business.

See rule, business.

A professional responsible for understanding the business processes and information needs of an organization, serving as a liaison between IT and business units, and acting as a facilitator for organizational and cultural change. See also systems analyst.

A method for defining an enterprise architecture and information systems architecture developed by International Business Machines Corporation (IBM) in the early 1980s.

See Body of Knowledge, Business Technology Architecture (BTABoK).

An event involving the exchange of products, money, and/or information.

Commerce transactions between equivalent businesses, such as between a wholesaler and a retailer.

Commerce transactions between a business and a consumer, such as in a retail sale.

Commerce transactions between a business and a governmental body, such as between a business and an elected water commission.

A single character of data stored electronically in 16 binary bits. A datum.

The term originally coined by International Business Machines Corporation (IBM) with the announcement of the 360 series of computers in 1974. Originally consisted of 8 bits; could be used to store a single character, digit, or two decimal digits (“packed decimal”), or in combination could be used to store numbers. ASCII and EBCDIC are the two dominant character coding schemes based on 8 bits.

A block of memory on a computing system for temporary storage of data likely to be used again.

A state when a data request can be supplied from data within a cache, rather than directly from disk storage.

A state statute to enhance privacy rights and consumer protection for residents of California.

The part of an organization that handles inbound/outbound telephone or email communications with internal and/or external customers. An information technology (IT) help desk is a call center for customers of the IT department.

Detailed tracking, reporting, and analysis that provides precise measurements regarding current marketing campaign efforts, their performance, and the types of leads they attract.

See Body of Knowledge, Canadian Information Technology.

See key, candidate.

A set of one or more columns that can uniquely identify each row in a table, providing that no subset of its columns can also uniquely identify the row. A table can have multiple candidate keys but only one is chosen as the primary key. The candidate key’s attributes can contain a NULL value that opposes the primary key.

See chart, candlestick.

An accepted principle or role; a body of principles, rules, standards, or norms by which something is judged.

A data model of the inherent structure of data without regard to applications, hardware, or software implementations. Built according to specific canons. Usually a result of canonical synthesis.

The concept that if everyone followed the canons (rules) for developing a data model, then those independent data models could be readily plugged together, just like a picture puzzle, to provide a single, comprehensive, organization-wide data architecture.

A system development process capability maturity model published by the Software Engineering Institute at Carnegie Mellon University. The CMM is a guide to improve an organization’s software development process, featuring defined practices used to rank an organization at one of five process maturity levels. Preceded by the Capability Maturity Model for Software. Commonly called Capability Maturity Model (CMM).

The maximum amount that can be held, contained, or processed at one time.

A number measured on a scale with an arithmetically meaningful zero point. Generally used to measure quantities or volumes. Can be manipulated by all the binary operators: exponentiation, multiplication and division, addition and subtraction, comparison (e.g., less than), matching, and Boolean. See also ordinal number; interval number; nominal number.

The number of entities or members in a set that may participate in a given relationship, expressed as one-to-one (1:1), one-to-many (1:M), or many-to-many (M:N).

A set of points on a set of axes used to show location or proximity.

In data processing, given two or more populations, the set of all possible combinations, taking one value from each population. Also called Cartesian join. Usually a large and meaningless answer set for an incorrectly phrased query.

See chart, cartogram.

The study and practice of making maps. Maps function as visualization tools for spatial data. Most quality maps are now made with geographic information system (GIS) software and databases.

See chart, cascade.

The declaration made on a hierarchical (one-to-many) relationship between parent and child, that a request to delete a parent instance will also result in deleting the related child instances. Usually associated with a foreign key (which defines a hierarchical relationship), with the referring entity table (where the foreign key is stored) being the child and the referenced entity table is the parent.

An evaluation of an instance of a process to determine what environmental or inherent attributes drove success or failure of the process.

Generally, a complete list of things, usually arranged systematically.

In databases, the component of a database management system (DBMS) where metadata about DBMS objects is stored. Most relational DBMS products keep the catalog as relational tables. The majority of metadata in a DBMS catalog is technical metadata (e.g., names, types, lengths, occurrences, keys) collected automatically by the DBMS software, although business definitions can be added as comments.

A (data) catalog is an active data dictionary.

The generic term for items at any level within a classification.

A scheme made up of a hierarchy of categories, which may include any type of useful classification for the organization of something.

See chart, causal loop diagram.

The relationship between cause and effect, which is important for understanding the impact of actions in artificial intelligence systems.

See chart, cause-and-effect diagram.

Generally, any small compartment.

In multidimensional design, a data point defined by one member of each dimension of a multidimensional structure. Often cells in multidimensional structures are empty, leading to “sparse” storage.

A team of people that promotes collaboration and use of best practices around a specific focus area to drive business results.

A centralized data management services organization of data management professionals.

The part of a computer that reads, interprets, and performs instructions.

See chart, distance cartogram.

A token of authorization or authentication.

In data security, a computer data security object that includes identity information, validity specification, and a key.

The process of reviewing something to verify it meets established standards.

A professional certification offered by TDWI (Transforming Data with Intelligence), using examinations developed and delivered by the Institute for Certification of Computing Professionals (ICCP).

Data that has passed data quality review, certifying it meets established standards.

A professional certification program offered by DAMA International, using examinations developed by DAMA International.

The documentation of ownership of something, from capture, through possession, storage, and management, to disposition. This is especially important for compliance documentation. See also data provenance.

Connecting a series of commands or responses.

In cryptography, a method of encryption where each block defines or contributes to the encryption of the following blocks.

The process of coordinating changes to a system in order to minimize change-related errors and therefore improve data quality and system availability. Proposed changes are reviewed and evaluated for related impacts, grouped and scheduled, and implemented and migrated through various test environments before being implemented into the production environment. Database change control disciplines are a very important responsibility of database administrators.

The process of capturing changes made to a production data source. Change data capture is typically performed by reading the log file of the database management system of the source database. Change data capture consolidates units of work, ensures data is synchronized with the original source, and reduces data volume in a data warehousing environment.

A distinguishing feature or quality.

Pertaining to, constituting, or indicating the character or peculiar quality of a person or thing; typical; distinctive.

An abstraction of a property of an object or of a set of objects.

See data entity, dependent.

A visual representation of data, using shapes, colors, symbols, graphs, images, tables, diagrams, etc. to show patterns, relationships, or ideas, that makes the data easier to understand or gives context to create some form of information.

A form of visualization that shows patterns of ideas or data by grouping them by topic or some attribute they share.

A chart showing multiple lines from left to right, each of which defines the top line of an area within the chart. The areas are marked with colors, textures, and/or hatching. The areas may be overlapping or stacked.

A chart that uses a geographic map of the world with the size of countries or their subdivisions distorted by the value of a property of that area, such as population.

A chart that shows bars to illustrate frequencies or values for individual categories.

A chart that displays five values of a measurement where the median and quartile values are the center and edges of a box, and the lowest and highest values are the ends of lines extending from the box.

A diagram illustrating steps necessary for two disparate positions to come to a consensus in a middle area, crossing some gap between them, usually illustrated by a bridge over a river or chasm.

A chart showing two dimensions on horizontal and vertical axes, and a third dimension in the size of the points.

A variation of the bar chart that compares a single, primary measure to one or more other measures, such as a target or a quantitative scale, displayed in qualitative ranges (poor, fair, good, etc.) by using variations of hue for a single color (which is helpful for colorblind vision). These long narrow graphs can be grouped to save space, especially on web forms or dashboards.

A chart showing bars representing range of value change within a point’s time interval.

A chart consisting of a geographic map modified to show some measurement of the map’s area, contents, or qualities. Modifications can be to color or to proportional size. There are two types: area cartograms and distance cartograms.

A chart with the X-axis showing a unit of measure and the Y-axis showing a rate per unit. Boxes show the result of X units × Y rate for a specific segment, such as customer. Tall thin boxes above the X-axis are desirable; long short boxes above the X-axis are less desirable; boxes below the X-axis are undesirable.

A visual representation of a system’s feedback loops, where positive loops cycle clockwise and negative loops cycle counterclockwise.

A chart that links an outcome to chains of possible contributing factors as a tree structure, working backward from an event to determine possible root causes, drawn sideways so that it resembles the skeleton of a fish. Because the chart resembles the skeleton of a fish, it is often called a fishbone diagram. A quality improvement concept invented by the Japanese statistician Karu Ishikawa.

A type of diagram that shows a system’s classes, contents, attributes, and relationships, including inheritance. UML is a common format for a class diagram.

A representation of objects and their links to each other, sometimes including time and/or sequence of relationships. Numbers show the sequence of activities or messages.

A visual representation of the parts of a whole, usually a system, with sequences of dependencies between components shown.

A form of visualization showing nested subsets of a set as circles within other circles, such as cities in states in countries in a total population, with each level represented as the area of one of the circles.

A form of visualization where a concept is decomposed into components to the right, “fanning” out levels.

A form of visualization showing relationships among concepts as arrows between labeled boxes, usually in a downward branching hierarchy. See also data model, conceptual (CDM).

A form of visualization that takes a tree diagram and turns it into a three-dimensional circle of attributes radiating from a parent.

A form of visualization for tracking process performance over time.

See chart, polar area.

A form of visualization of the critical path for a set of interdependent activities, showing the longest discrete path through the tasks with the longest duration.

A form of visualization showing cycles of a concept’s stages, phases, or process steps in a clockwise path around a circle. Also called cycle diagram.

A form of visualization using a geographic map with overlaid data shapes using colors to illustrate ranges of values for each geographic block.

A graph of decisions and their possible consequences (including resource costs and risks) used to create a plan to reach a goal. Decision trees are a special form of tree structure constructed to help with making decisions. Regression trees approximate real-valued functions (e.g., estimate the price of a house or a patient’s length of stay in a hospital). Classification trees define the logic for categorization using Boolean variables such as gender (male or female) or game results (lose or win).

A chart consisting of a geographic map modified to show some relative travel times between points in a network.

A form of visualization showing one pool of two fixed resources shared by two entities. Each point shows a possible division of resources between the entities. Curves can be drawn between points of equal value to both parties according to the value associated with each resource. Named for creator Francis Ysidro Edgeworth.

A form of visualization that follows a process from a desired input through possible system events to final consequences. See also chart, fault tree.

A form of visualization showing top-down, deductive analytical steps through Boolean logic gates to all possible failure states. Also called failure tree.

A form of visualization where a topic appears in the center and forces for and against the topic are listed on each side.

An outline or hierarchy diagram depicting the hierarchical decomposition of processes into their component processes. A functional decomposition can be depicted vertically as an outline or horizontally as a hierarchy chart.

A form of visualization where inputs are drawn entering through the large end of a funnel and outputs are drawn leaving the small end.

A horizontal bar chart used in project management; a graphical illustration of a schedule that helps to plan, coordinate, and track specific tasks in a project. Named for Henry Gantt.

A form of visualization that divides the process of adoption of something into five cycles: trigger, peak, trough, slope, and plateau.

A form of visualization that uses a quartered chart comparing companies selling similar products according to their completeness of vision and ability to execute on that vision. The quarters are leaders (high on vision and execution), challengers (high on execution, low on vision), visionaries (high on vision, low on execution), and niche players (low on both vision and execution). Developed by Gartner, Inc., to evaluate vendors in specific market segments.

A chart where one set of values is represented by areas of rectangles and other sets of values are represented by colors. Used to look at large, fast-changing sets of structured data. In this chart, the size of a rectangle reflects its importance and color conveys the speed of change. Heat maps are often used in applications to monitor and analyze changes in stock market and portfolio data in financial services applications. Invented by Ben Shneiderman at the University of Maryland. See also chart, tree map.

A form of visualization showing positive and negative effects of some system or action by illustrating the positive items at the top as “heaven,” the negative at the bottom as “hell,” and neutral items in the center.

A form of visualization where a tree is displayed in a circular manner as a node-link diagram radiating out from the root rather than only descending. Also called hypertree.

A form of visualization with a medial line dividing attributes into two categories: visible and invisible (or hidden). The visible attributes are listed above the line (the visible part of the iceberg); the invisible attributes are listed below the line (the hidden part of the iceberg).

A chart showing movement of a value regardless of time, based solely on some time-independent criteria.

Shows the decomposition of some object or system by exposing internal layers sequentially.

A form of visualization of a process or system over time compared to value at each point in time, grouped into four stages: research and development (R&D)/initiation, ascent, maturity, and decline.

A chart that shows ordered points connected by a line to show trends.

A chart with the X-axis showing a list of values within a category (such as a list of business units) where the width is each bar’s relative magnitude compared to the others and the Y-axis showing percentages or ratios. Each value is then a stacked area chart with each area shown as a percentage of the total for that X value. Named for printed fabric patterns typical of Finnish company Marimekko. Also called Mekko chart, matrix chart, eikosogram.

A chart showing movements in a value over time at different points within each time grain, using both lines and bars. This chart shows values for high and low separate from those for start and end of each time period point on the chart.

A form of visualization showing the structure of an organization using trees and levels to show relative hierarchies of teams or individuals.

A form of visualization showing a series of vertical parallel lines representing dimensions or axes, and horizontally oriented lines intersecting points on those exes. During development, the ordering of the vertical axes may need to be shifted to better show patterns in the coordinates.

A chart showing both bars and a line, where the line shows the cumulative total of the individual bars going left to right. Named for Vilfredo Pareto.

A form of visualization using a series of horizontal lines, each representing an evaluation range of a specific quality. A set of processes or performances is evaluated against the lines, and the points of the evaluations are connected into a line for each process or performance.

A form of visualization resembling looking down into a box, with the floor of the box being the main topic, the left and right side panels representing positive and negative input or experiences, the bottom side panel representing prior knowledge or experience, and the top side representing open questions or issues.

A form of visualization for distributed systems, using bars and circles to represent events and conditions respectively. Directional arrows show the path between the events and conditions in the system. Named for Carl Adam Petri. Also called place/transition net, P/T net.

A form of visualization that shows percentages as sectors (slices) of a circle, resembling a pie.

A form of visualization showing a circle with sectors, using radius length of sectors to show relative differences. May have multiple sections to each sector to compare multiple values.

A framework for evaluating strategic positions, using five forces: threat from competitors, threat of substitute products or services, bargaining power of customers, bargaining power of suppliers, and barriers to entry. Named for Michael Porter.

A quartered plot chart used most frequently to determine priorities in business, using growth rate on one axis and market share as the other. Creates four categories: stars (high growth and high market share), cash cows (low growth, high market share), dogs (low growth and low market share), and question marks (high growth and low market share).

A visual representation of how control moves between logical processes (how the end state of a process serves as the start state for other processes).

A visual representation showing three or more quantitative values represented on radial axes of a circle.

A two-dimensional representation of values of a dataset. Usually used to show dependency of one uncontrolled variable vs. another controlled variable.

A form of visualization consisting of vertices (concepts) and directed or undirected edges (relationships).

A representation of the time sequence of objects participating in a process over time. Swimlane charts are a form of sequence chart.

A form of visualization showing trends and variations of multiple measurements over time in one chart.

A form of visualization using a time-varying image that shows the spectral density of a signal over time, using horizontal axis as time, vertical axis as frequency, and hue of the representation as amplitude.

A form of visualization where a project appears in the center and stakeholders are illustrated in terms of proximity of responsibility to the project. Internal stakeholders are above a central line through the project, and external stakeholders are below the line.

A form of visualization using a quartered chart to show stakeholders in terms of importance and influence.

A visual representation of a system where quantities of something travel through the system from point to point over time.

A form of visualization used to document strategic goals from multiple perspectives.

A form of visualization that plots price vertically and quantity horizontally. The supply curve (usually trending upward left to right) shows the price per quantity offered by a supplier. The demand curve (usually trending downward left to right) shows the price per quantity desired by consumers. Equilibrium is the intersection of both curves.

A form of process flow diagram that shows involvement over time within the process for multiple equivalent actors, such as teams, departments, and systems.

A form of visualization that matches goals of different time horizons with the specific technologies necessary to meet or enable those goals.

A form of visualization showing an image with a foundation and two or more pillars supporting a roof, with or without a cloud of distantly related topics. The foundation contains fundamental elements, the pillars group supporting elements, and the roof includes overarching topics that cover all the pillars/groups.

A chart showing a horizontal line or bar containing points labeled with dates and/or events.

A method of representing a hierarchical set of data in a graphical form, with fewer nodes at the either the top (i.e., descendent genealogy) or bottom (i.e., ancestor genealogy).

A chart where one set of values is represented by areas of rectangles and other sets of values are represented by colors. Used to look at large, fast-changing sets of structured data. In this chart, the size of a rectangle reflects its importance, and color conveys urgency (blue shades for positive, red shades for negative). Invented by Ben Shneiderman at the University of Maryland. See also chart, heat map.

A form of visualization showing actors and roles when interacting with objects in defined scenarios. UML and flowcharts are common formats for use-case diagrams.

A form of visualization that shows a problem, the steps to planning a solution, and then the steps to evaluate the results afterward. Shaped like the letter v; hence the name.

A form of visualization that shows all potential logical relationships between a finite set of objects. Used most often to illustrate the concepts of UNION, INTERSECTION, and EXCLUSIVE OR of sets. Named after John Venn.

A chart that shows cumulative effects of sequentially applied values.

A statement of objectives, scope, and stakeholders or participants in a project or program.

An AI–powered conversational agent designed to simulate humanlike interactions and provide answers to user queries in natural language.

A generative pretrained transformer (GPT) artificial intelligence chatbot developed by OpenAI, Inc. This large language model interacts in a dialogue format and can answer questions in natural language. The model imitates human behavior and is trained using reinforcement learning from human feedback.

An extra digit added to a computer code to check accuracy, calculated from the other digits in the code. See also parity.

A synchronization step between a data system and an application where all changes to the data system are recorded to disk and noted as complete.

A copy of the state of a system at a point in time.

A corporate officer who is responsible for managing the enterprise’s data assets.

An executive data steward who serves as the chair of the data governance council and the primary business champion of a data management program.

The head of the information technology (IT) group within an organization. Often reports to the chief executive officer. The prominence of this position has risen greatly as IT has become a more important part of organizations.

An organizational leader responsible for ensuring that the organization maximizes the value it achieves through the organization’s collective knowledge: its intellectual capital (including patents), the skills and experience of its people, the maturity of its processes, and its customer relationships. The CKO is responsible for managing these intangible assets through knowledge management, fostering innovation, sharing best practices, facilitating communication, and avoiding knowledge loss after organizational restructuring.

The executive accountable for discovery and governance of significant risks (strategic, reputational, operational, financial, or compliance-related) to an organization and related opportunities. Data governance is a form of risk management and may be part of this executive’s organization. Also called chief risk management officer.

An executive position focused on technical issues in an enterprise. In technical industries, the CTO heads research and development. In other enterprises, the term is sometimes synonymous with chief information officer (CIO).

See chart, pie.

A person recognized as a member of a public state, with associated obligations and rights. Not the same as customer.

Solutions for capturing and maintaining accurate, up-to-date data about individual citizens and delivering information in an actionable form “just in time” at citizen touchpoints. A specialized form of master data management focusing on citizen master data.

Establishing relationships with individual citizens and then using that information to treat different citizens differently. Census profiles and taxpayer analysis are examples of decision-support activities that can affect the success of citizen relationships. Effective CRM is dependent on high-quality master data about individuals and organizations; see citizen data integration (CDI).

A measurement that evaluates freedom from obscurity or extraneous data.

A type or category of things with common attributes. Members of a class conform to the definition of the class. Type and category are synonyms for class. Classes are the basis for object-oriented analysis, design, and development, where a class is roughly equivalent to an entity with the addition of described functional behavior. See also method.

A set of objects that share the same attributes, operations, methods, relationships, and semantics.

A class diagram resembles an entity relationship (ER) diagram, but the operations or methods section is not present in an ER. See also chart, class diagram.

A word used in an attribute’s name to show what type of data is contained therein, usually applied at the end. See also prime word.

In .NET framework, developed by Microsoft, associates information with a target element.

In .NET framework, developed by Microsoft, associates information with local system processes.

Represents the security level that can be assigned to users.

The traditional, top-down comprehensive approach to implementing business intelligence, including: building an enterprise data model, defining the data warehouse architecture, designing and constructing the physical database, designing and constructing and testing extract-transform-load programs, and populating the database using current sources and historical data conversions. Used in contrast to incremental data warehouse development.

Generally, a set of discrete, exhaustive, and mutually exclusive observations that can be assigned to one or more variables to be measured in the collation and/or presentation of data.

In data modeling, the arrangement of entities into supertypes and subtypes.

In object-oriented design, the arrangement of objects into classes and the assignment of objects to these categories.

In artificial intelligence, a supervised learning task where the model predicts categorical labels for input data.

Arrangement or division of objects into groups based on characteristics that the objects have in common.

In data management, how data is stored, accessed, and processed by separating responsibilities between two types of systems: clients and servers.

In client/server programming, a software program used to contact and obtain data from a server software program on another computer. Each client program is designed to work with one or more specific kinds of server programs.

See architecture, client/server.

A more familiar name for the Information Technology Management Reform Act of 1996, a US federal law coauthored by Congressman William Clinger and Senator William Cohen, designed to improve the way the federal government acquires and manages information technology (IT). It requires departments and programs to use performance-based management principles for acquiring IT and mandates the use of a formal enterprise architecture for all federal agencies.

See architecture, closed.

An architecture in which all access to shared resources is provided on demand via self-service internet applications. Formerly known as distributed computing. The cloud is used heavily in large-scale analytics and in data science applications.

Services that are made available in a distributed computing (cloud) environment.

See index, clustered.

To store data physically adjacent (in sequence) on a disk, based on a clustering index.

A data science methodology involving finding groups in a given dataset, usually using the distances among the data points as a similarity metric.

Generally, a language-independent set of letters, numbers, or symbols that represent a concept whose meaning is described in a natural language.

In software, the program language lines of instruction that make up software.

In data modeling, a shorthand key value representing the domain value of an attribute. Code sets are intensional domain value sets.

To represent data in a form that can be accepted by a data entry program.

The definition and maintenance of coded data values, descriptions, definitions, cross-references, parent–child rollups, and other relationships for the valid instances of limited (intensional) domains. Code management is a specialized form of master data management. It is a key responsibility of operational data stewards because it has a very significant impact on overall data quality. Code management typically includes an approval process for all code value additions, changes, and retirements.

The definition and maintenance of program code for the purposes of controlling development on production systems.

A relational database table containing rows for each valid value in a finite domain. Code tables contain some form of encoded data values. Code tables are reference data, maintained through code management.

The process of converting verbal or textual information into codes representing classes within a classification system, to facilitate data processing, storage, or dissemination.

The assignment of an incorrect code to a data item.

In software, an error in program lines of instruction that make up software or data transformation routine.

Systems and applications that simulate human processes and mimic the functions of the human brain through self-algorithms using data mining, pattern recognition, and natural language processing.

A close working relationship between parts, complete enough when together to enable some degree of autonomy without other extraneous parts.

See backup, cold.

A recommendation technique that predicts a user’s interests by collecting preferences from many users.

The assembly of documents or data entities or attributes into a standard order, such as alphabetical.

In data modeling, a data attribute as implemented in a relational database as a vertical component of a table, similar to a field in a flat file record.

See database, columnar.

See database, column-oriented.

See key, composite.

In data modeling, supplementary descriptive text that can be attached to data or metadata.

Acronym to identify software that is used as-is, without any customization.

The SQL statement that concludes a unit of work (database transaction).

See Body of Knowledge, ISC2 Common.

A single, formal, comprehensive, organization-wide data architecture that provides a common context within which all data is understood, documented, integrated, and managed. It transcends all data at the organization’s disposal and includes primitive and derived data; atomic and combined data; fundamental and specific data; automated and nonautomated (manual) data; current and historical data; data within and without the organization; high-level and low-level data; and disparate and similar data. It includes data in purchased software, custom-built application databases, programs, screens, reports, and documents. It includes all data used by traditional information systems, expert systems, executive information systems, geographic information systems, data warehouses, object-oriented systems, and so on. It includes centralized and decentralized data regardless of where they reside, who uses them, or how they are used.

A standard protocol that defines web server delegation of web-page generation to console applications, known as CGI scripts.

The Object Management Group vendor-independent architecture and infrastructure for object-based programming interoperability. See also Common Object Model.

A form of UML (Unified Modeling Language) diagram that shows the interactions between objects or parts in terms of sequenced messages. Each message is numbered regardless of its placement on the diagram so that the reader can follow the path by following the numbers sequentially.

All professionals and other stakeholders with active interest and role within a community. See also data management community of interest.

The extent to which differences between statistics can be attributed to differences between the true values of the statistical characteristics.

A technology for building and managing information systems. The goal of CEP is to enable the information contained in the events flowing through all of the layers of the enterprise information technology infrastructure to be discovered, understood in terms of its impact on high-level management goals and business processes, and acted upon in real time. This includes events created by new technologies such as radio-frequency identification (RFID).

The act of agreement to follow external government or industry regulations.

The process of conforming, completing, performing, or adapting actions to meet the rules, demands, or wishes of another party.

A discrete object or entity that is a part of a larger system.

A modular part of a system that encapsulates its content, and whose manifestation is replaceable within its environment.

A collection of software that can be installed and replaced as a unit.

A content management system that manages low-level objects (image, table, etc.) rather than higher-level documents.

See chart, component diagram.

Microsoft Corporation’s programming specification for object interoperability through sets of predefined routines called interfaces.

See data attribute, composite.

See key, composite.

A model that includes other models and the relationships between them.

See partitioning, composite.

See key, composite.

The study of using computational methods to process and analyze human language.

The use of software tools (CASE tools) to assist in the development and maintenance of software. All aspects of the software development lifecycle can be supported by software tools, so tools for project management, business and functional analysis, system design, code storage, compiler translation, and testing can all be considered CASE tools. Sometimes more broadly referred to as computer-aided systems engineering.

An old-fashioned term for the management of metadata between the encyclopedias of multiple CASE tools, of the same type or different types.

Automated modeling tools for used model-driven systems planning, analysis, design, and development. “Upper CASE tools” are modeling tools used for planning, analysis, and high-level logical design. “Lower CASE tools” are used for program design, code generation, version control, and testing. Data modeling tools may be both upper and lower CASE tools.

Video, images, and printed media created with computer graphics applications.

A subfield of artificial intelligence that enables machines to interpret and make decisions based on visual data, such as images and videos.

See electronic health record.

See key, composite.

See data model, conceptual (CDM).

See model, conceptual.

Including only necessary parts; not including unnecessary details or attributes.

The simultaneous execution of processes against the database.

The control of process contention for resources within multi-process systems.

The ability of one process to see information about other processes that are executing at the same time.

See chart, cone tree.

The space between an upper and lower limit of a range, where there is a high probability of the inclusion of a particular value.

A measurement of certainty that a statistical prediction is accurate.

In artificial intelligence, a probability-like measure indicating how sure the model is about a given prediction.

Ensuring that information is accessible only to those authorized to have access.

In data security, a property of data indicating the extent to which its unauthorized disclosure could be prejudicial or harmful to the interest of the source or other relevant parties.

A generic term often used to describe the whole of the activities concerned with the creation, maintenance, and control of databases and their environments.

Agreement to follow internal policies, standards, procedures, and architecture requirements.

A dimension that means and represents the same thing when linked to different fact tables.

The state of being similar to accepted standards or to the attributes of peers.

The process of becoming similar to the attributes of peers or to a standard.

The characteristic of a graph in which there exists at least one path from every node to every other node in the graph.

The agreement of a group to a decision, judgment, or definition, when all stakeholders present can say, “I can live with it.”

Uniformity or agreement among things or parts of things. Having internal logical and numerical coherence; having no internal contradiction.

The process of combining and aggregating data from different systems and possibly disparate formats to create a unified view of information.

Generally, a restriction on a business action and the resulting data. For example, “Only wholesale customers may place wholesale orders.”

In data management, a specification of what may be contained in data or a dataset in terms of the content or, for data only, in terms of the set of key combinations to which specific attributes (defined by the data structure) may be attached, and how. Examples include dependency (must have at least one), exclusivity (at most one; non-overlapping), subset, or equality.

A type of constraint on an attribute that defines the values that may be assigned, through limits, lists, or ranges.

A type of constraint on a dataset that restricts the combinations of attribute values according to certain rules (e.g., uniqueness).

The information contained within documents and web pages.

The name of a DCMI element set (Coverage, Description, Type, Relation, Source, Subject, Title). See also Dublin Core Metadata Initiative (DCMI).

The processes, techniques, and technologies for the organizing, categorizing, and structuring of information resources so that they can be stored, published, and reused in multiple ways. Content management is a critical data management discipline for data found in text, graphics, images, and video or audio recordings.

A system used to collect, manage, and publish information content, storing it as components or whole documents, while maintaining the links between components. It may also provide for content revision control.

See mashup, content.

A DAMA International policy stating the organization’s intention to avoid reference to specific technology vendor firms and their products. Also referred to as vendor neutrality.

Generally, facts or circumstances that relate to a situation or event.

In software design, the minimal set of data required for a task that allows interruption and resumption of the task without error.

See model, contextual.

The process of adding language to signal relevant aspects of an event or data attribute.

See relationship, contingent.

A ready state of functionality that seeks to guarantee computing-system operation despite any challenging event. Continuous availability requires seamless availability during any planned or unplanned event and seamless recovery of applications, data, and data transactions committed prior to the event.

Shows the transition of a topic from one extreme to the other, and all interesting points in between. Usually shown on a double-headed arrow, with each end being one extreme.

An element in DCMI element set Intellectual Property: an entity that contributes to a resource. See Dublin Core Metadata Initiative (DCMI).

The mechanism used to maintain acceptable performance of a process.

See chart, control.

Data that guides a process, such as indicators, flags, counters, and parameters.

The minimum or earliest acceptable value in a range of acceptable values.

The maximum or latest acceptable value in a range of acceptable values.

A defined list of explicitly allowed terms and their definitions. The organization of a controlled vocabulary into a parent–child hierarchy is a taxonomy.

In systems, the migration from use of one application to another.

In data management, the process of preparing, reengineering, cleansing, and transforming data and loading it into a new target data structure. Typically, the term is used to describe a one-time event as part of a new database implementation. However, it is sometimes used to describe an ongoing operational procedure.

A type of deep learning model particularly effective for image processing and recognition tasks.

An identifier used by a web application to associate a present website visitor with their previous activity with that company.

A style of application processing in which presentation, business logic, and data management are split among two or more software services operating on one or more computers. In cooperative processing, individual software programs (services) perform specific functions that are invoked by means of parameterized messages exchanged between them.

A business data steward with additional responsibility for

• leading data stewardship teams and
• representing data stewardship issues and integrating team models and specifications on a data stewardship committee (DSC).

The set of exclusive privileges granted to an author, creator, or owner of a work and allowing control or use of that work, including copying, distribution, and adaptation of the work.

An architecture promoted by Bill Inmon that describes the complete data lifecycle within an organization through multiple layers and components of architecture in order to satisfy both operational and analytical needs.

See business performance management.

A predictive relationship between two factors, such that when one factor changes, the nature, direction and/or amount of change in the other factor can be predicted. Not necessarily a cause-and-effect relationship.

See database, correlation.

A function that describes the correlation of the values of a dataset to a line.

Comparison of the estimated value of business benefits over time to the estimated cost of expenditures required to realize these benefits.

A DCMI element in element set Content: the topic, jurisdiction, or spatial scope of a resource. See Dublin Core Metadata Initiative (DCMI).

See index, covering.

An internet bot that uses search engines to carry out automatic search and retrieval of selected information on behalf of a user. Also called web crawler.

In the context of data, a process of systematically scanning data sources to extract valuable metadata from those sources.

The only functions of data in persistent storage, with a convenient acronym form.

An information value chain analysis tool. It documents that a given organization, role, process, or application creates, reads, updates, and/or deletes data in a given subject area, entity, or attribute. CRUD matrices are the vehicle for information value chain analysis. Each of the many different kinds of CRUD matrices establishes the link between a data model and another model (data-to-process, data-to-organization, or data-to-application).

The date on which the record, data, or metadata item was created.

A DCMI element in element set Intellectual Property: an entity that is responsible for the first existence of a resource instance. See Dublin Core Metadata Initiative (DCMI).

See chart, critical path Method.

One of the most important prerequisite conditions necessary for an enterprise to reach its goals.

Of interest to more than one organization in an enterprise, especially of data or process.

The practice of suggesting the purchase of a related product to customers who are already making a purchase.

Cross-referencing of data from one or more sources for analysis or reporting.

A tag language that enables authors to associate formatting style (fonts, spacing, and aural cues) to structured documents, including HTML and XML applications.

See data cube.

A medium of exchange, usually a form of money.

Monetary denomination of the object being measured.

The degree to which data represents reality as of a point in time.

A date when the data is considered valid. Also known as currency date or the “as of” date.

A person or organization whose needs are important to the enterprise or person, and whose satisfaction with the products and services provided by the enterprise determines its success, failure, and effectiveness. See also citizen.

Solutions for capturing and maintaining accurate, up-to-date data about individual customers and delivering information in an actionable form “just in time” at customer touchpoints. A specialized form of master data management, focusing on customer master data. See also citizen data integration (CDI).

Establishing relationships with individual customers and then using that information to treat different customers differently. Customer buying profiles and churn analysis are examples of decision-support activities that can affect the success of customer relationships. Effective CRM is dependent on high-quality master data about individuals and organizations; see customer data integration (CDI). See also citizen relationship management (CRM).

Any type of internet-based promotion through websites, targeted email, internet bulletin boards, e-commerce, and online social networking mechanisms.

A metaphoric abstraction for a virtual reality existing inside computers and on computer networks. While cyberspace should not be confused with the real internet, a website might be said to “exist in cyberspace.” According to this interpretation, events taking place on the internet are not therefore happening in the countries where the participants or the servers are physically located, but instead are happening “in cyberspace.”

See chart, cycle graph.

The time required to execute a process from start to finish.

The former research and education affiliate of DAMA International, with a mission to promote development of a formal, certified, recognized, and respected data management profession.

An international not-for-profit association of data management professionals with chapters and members around the world, dedicated to advancing the concepts and practices of managing data, information, and knowledge as enterprise assets. Founded in 1980 as the Data Administration Management Association, DAMA International is the leading data management professional organization worldwide.

The organizing structure consisting of a functional decomposition of ten data management functions mapped against six environmental factors.

An umbrella term for content that exists on darknets. Darknets use the internet but require specific software, configurations, or authorizations to access. Through the dark web, private computer networks can communicate and conduct business anonymously without divulging their location.

A business intelligence application that consolidates, aggregates, and graphically presents performance measurements compared to goals, arranged so that information can be monitored at a glance. Dashboards can be used to manage any scope of operations.

A representation of facts, concepts, or instructions in a formalized manner suitable for communication, interpretation, or processing by human beings or automatic means.

Individual facts that are out of context and have no meaning by themselves. Often referred to as raw data. The word data is plural in form, but it can be singular or plural in construction.

Subject-oriented, integrated, time-variant, nonvolatile collections of data in support of business intelligence activities. See also online analytical processing.

A dataset created through a computational step applied to atomic data. Derived data is the result either of relating two or more attributes of a single transaction (such as an aggregation) or of relating one or more attributes of a transaction to an external algorithm (formula) or rule. See also data attribute, derived.

Data not structured in a relational database table or grid format. Includes unstructured data, which has different internal structures, but can include links as well as classification tags as part of the tabular data attributes. See also data, unstructured.

Process-oriented, nonintegrated, time-current, volatile collections of data used to support the daily activities of an enterprise. See also online transaction processing (OLTP).

Data that can be described using a discrete domain of vocabulary terms, organized by inherent patterns into semantic groups or entities, presented by context rather than content.

Data stored in grid (or table) format (records or rows, and columns).

Data that has not been tagged or otherwise structured into rows and columns or records, including documents, files, graphics, images, text, reports, forms, video or sound recordings, social media content, web pages or blogs, engineering and design CAD/CAM files, genomics and scientific sequencing data, and internet of things and machine-generated data. This term has some inaccurate connotations, as there is usually some structure (for instance, paragraphs and chapters) in these formats.

The formal, sometimes highly rigorous, process associated with acknowledging that data has been delivered or accepted for use in an acquiring system or organization.

The degree to which a data attribute value closely and correctly describes its business entity instance (the “real life” entities) as of a point in time.

The collection of processes of identification, selection, and mapping of source data to target data, including detection of source data changes, data extraction techniques, timing of data extracts, data transformation techniques, frequency of database loads, and levels of data summary.

The activity performed to obtain data, or have access to it under either limited or unlimited rights for use.

The organization and management of data in multiple types of storage, including databases, spreadsheets, and image or content management systems.

An individual or organization responsible for specifying, acquiring, and maintaining software for data management, and the security and validation of the contents, including the data dictionary and data models.

The study and presentation of data to create information and knowledge.

A business systems analyst who identifies data requirements, defines data, and develops and maintains data models.

A type of data de-identification where personal identities are removed so individuals cannot be reidentified.

A combination of hardware, software, database management system, and storage that cannot be viewed or inspected and that yields high performance in both speed and storage and makes data access simpler.

Servers built specifically for data transformation and distribution. These servers integrate with existing infrastructure either directly as a plug-in or peripherally as a network connection.

A master data analyst, responsible for the overall data requirements of an organization, its data architecture and data models, and the design of the databases and data integration solutions that support the organization.

See architecture, data.

The degree to which data models and database designs are stable, flexible, reusable, aligned with enterprise goals, and supportive of data integrity.

The definition and modeling of the information needs of the enterprise and the designs to meet those needs. Includes information needs analysis, enterprise data modeling, definition of related data architecture, and project-related conceptual, logical, and physical data modeling. Physical database design is considered part of database management.

A master set of data models and design approaches identifying the strategic data requirements and the components of data management solutions, usually at an enterprise level. Typically consists of:

• an enterprise data model (contextual/subject area, conceptual or logical);
• state transition diagrams depicting the lifecycle of major entities;
• a robust information value chain analysis identifying data stakeholder roles, organizations, processes, and applications; and
• data integration architecture identifying how data will flow between applications and databases.

The data integration architecture may divide into database architecture, master data management architecture, data warehouse and business intelligence architecture, and metadata architecture. Some enterprises also include

• lists of controlled domain values (code sets), and
• responsibility for the assignment of data stewards to subject areas, entities, and code sets.

The enterprise data architecture is an important part of the larger enterprise architecture that includes business, process, and technology architecture.

The process that supports long-term storage of scientific data and methods used to read or interpret it. Data archival is a step along the path of data preservation and can be phased for online, near online, or offline storage availability. The data archival process is an important part of data migration and data refresh.

A model of delivering data where a provider licenses access via web-based servers for on-demand use.

Any data resource with organizational value.

Most prevalently used in geosciences, the process of combining data samples having specific sample criteria with projected data from a model to create and improve a unified consistent physical system definition.

Data that is written to and contained in static storage.

An inherent fact, property, or characteristic describing an entity or object; the logical representation of a physical field or relational table column. A given attribute has the same format, interpretation, and domain for all occurrences of an entity. Attributes may contain adjective values (red, round, active, etc.).

A unit of data for which the definition, identification, representation, and permissible values are specified by means of a set of characteristics.

A representation of a data characteristic variation in the logical data model or physical data model. A data attribute may or may not be atomic. See also attribute.

The set of possible values for an attribute. The values must conform to the definition of the attribute (such as type or size), and may be expressed by enumeration or by any combination of ranges and individual values, including values and ranges that are excluded from the set.

An instance of an attribute type or domain.

A composite attribute is one that is composed from the concatenation of other attributes.

An attribute created via calculation from some other attribute(s), either within the same object or within a linked or referenced object. See also data, derived.

An attribute or data item that can have multiple values (instances) for an instance of the entity of which it is an attribute. Such an arrangement forms a many-to-many relationship between the entity type and the attribute type, unless each unique value of the attribute can only be associated with at most one instance of the entity, in which case it forms a hierarchical relationship (one-to-many).

An attribute where history is not preserved. All changes overwrite the attribute at the time of the change.

An attribute where all history is preserved by requiring new rows be written that include the new data. The row with the old data is untouched except to update an expiration date or current row indicator.

An attribute where some history is preserved within the same record or row, in separate columns. When new data arrives, old data is moved to other columns within the same row, and the new data overwrites the old data in the column assigned to hold the current value.

The evaluation of data based on defined criteria. Typically used to ensure compliance with contractual and methodological requirements.

The process of artificially increasing the size of a dataset by creating modified versions of existing data.

The extent to which data is accessible when required.

The service-level agreement specifying expected uptime and accessibility for data systems.

The appropriate trade-off between accessibility, quality, security, and the cost of data.

Systematic distortion or imbalance in data that affects fairness or accuracy

An incident that exposes sensitive, personal, or confidential data to unauthorized individuals.

An entity or system that collects, aggregates, and sells or shares data.

The process by which collected data is put into a machine-readable form.

In relationships, the characteristic of a relationship that specifies the upper and lower bounds of how many instances of one entity or object type can be related to each instance of the same or some other entity or object type. Cardinality is separately specified at each end of the relationship. At each end the choices are 0, 1, or M. Combining the cardinality at both ends of a binary relationship yields 3 × 9 – 1 = 8 possibilities (0:0 is not a valid option).

A curated inventory of data assets with metadata, definitions, and usage guidance.

The process of creating, maintaining, and curating a data catalog.

An organization that values data as an asset and manages data through all phases of its lifecycle.

The process of verifying and stating that a dataset’s contents meet expected standards. See also certification.

Processes ensuring that changes to data or related systems are property documented, tested, and approved.

The attributes of data such as data type, associated metadata, and key data elements.

Activity through which the correctness conditions of the data are verified.

Categorizing data based on sensitivity, importance, or usage policies.

A label indicating sensitivity or security requirements (e.g., Public, Internal, Confidential).

The process of correcting data errors to bring the level of data quality to an acceptable level for information user needs.

A copy of data used for testing, development, or backup purposes.

The process of partitioning the data attributes of an entity or table into subsets or clusters of similar attributes, based on subject matter or characteristic (domain).

Operations performed on data to derive information according to a given set of rules.

The degree to which data is captured.

Compares the attributes implemented in a database against all known requirements.

A measure of the absence of null values for a database column.

Algorithms or techniques that change data to a smaller physical size that contains the same information.

The process of changing data to be stored in a smaller physical or logical space.

Protection of data from unauthorized access or disclosure.

The degree to which one set of attribute values matches another attribute set within the same row or record (record-level consistency), within another attribute set in a different record (cross-record consistency), or within the same record at different points in time (temporal consistency).

A person or group that receives data (on a screen, in a report, or through a query) and uses the data to create information. See also information consumer.

Structure defining the standards, roles, and mechanisms to ensure data is properly managed.

The process of changing data structure, format, or contents to comply with some rule or measurement requirement.

The process of changing data contents stored in one system so that it can be stored in another system or used by an application.

Errors, inconsistencies, or damage rendering data inaccurate or unusable.

A person who enters or updates data. Roughly equivalent to data producer. See also create-read-update-delete (CRUD).

A multidimensional data structure that contains an aggregate value at each point (i.e., the result of applying an aggregate function to an underlying relation). Data cubes are used to implement online analytical processing (OLAP). See also schema, star.

The active management of data through its lifecycle to ensure quality and usability.

See data steward.

Often called dedup for short, a feature that can help reduce the impact of redundant data on storage costs. Duplicated portions of the volume’s dataset are stored once and are (optionally) compressed for additional savings.

Statements that specify the business meaning associated with a conceptual, logical, or physical data entity or attribute.

The process of creating business metadata, including names, meanings, integrity rules, and domain values.

In computer programming, the statements in a computer program that specify the physical attributes of the data to be processed, such as location and quantity of data.

The degree to which data definitions are complete, accurate, current, correct, meaningful, thorough, and useful.

Making data broadly accessible to nontechnical users while maintaining governance and controls.

The process of introducing some redundancy into previously normalized databases with an aim of optimizing database query performance.

A relationship in which one data element or process relies on another.

The statements in a computer program that specify the physical attributes of the data to be processed, such as location and quantity of data.

A data model, an architecture model, or a descriptive representation of any complex object.

Analysis, design, implementation, testing, deployment, and maintenance of data.

Any place where business and/or technical terms and definitions are stored. Typically, data dictionaries are designed to store a limited set of available metadata, concentrating on the names and definitions relating to the physical data and related objects of systems implemented or in development. See also repository.

A data dictionary that interacts with its software environment to capture and update metadata in real time.

A store for metadata for multiple software tools. See also repository.

A data dictionary that requires batch or user entry and update of metadata.

The process of locating, identifying, and understanding available data assets.

The secure destruction or deletion of data at the end of its lifecycle.

In data storage, the mathematical patterns of data values as they exist within a set.

In data networks, the patterns of storage of data within and through various systems and on various platforms or sites.

In data movement, transmission of data to one or more locations from a central point.

The use of data mining to uncover relationships in data that may be valid within a test set but are not valid within the wider population. Sometimes used to deliberately generate misleading conclusions. Also called data fishing, data snooping.

Gradual change in data meaning, structure, distribution, or quality over time.

The presence of redundant copies of data.

Activity aimed at detecting and correcting errors, logical inconsistencies, and suspicious data. Data editing is the physical application of data integrity rules, which are developed logically and denormalized within the data to produce data edits, which are then applied to the data.

See data attribute.

The process of converting plain text or data into an unreadable format, known as ciphertext, using an algorithm and an encryption key. This ensures only authorized parties with the corresponding decryption key can access and read the original data.

An encryption program. See also encryption.

A classification of objects found in the real world – that is, the noun part of speech: persons, places, things, concepts, and events – of interest to the enterprise. Usually expressed in singular form.

An entity or table that resolves a many-to-many relationship between two other related entities or tables.

In a relational model, a child entity of another parent entity that cannot exist on its own.

A diagram that shows the arrangement and relationships between data entities. It contains only data entities and the data relations between those data entities. It does not contain any of the data attributes in those data entities, nor does it contain any roles played by the data attributes.

In software as a service, the practice of keeping a set of data with an independent third party to prevent data loss.

The process of sending and receiving data.

The process of examining data in order to determine ranges and patterns within the data.

The process of extracting information from a database into a file.

The result dataset from the export process.

A snapshot copy of data from a source database used to update data in a target database, or for use in an application.

To copy data from a source for data movement and data transformation.

The date data was extracted from a source database.

The latency of data extracts, such as daily versus weekly, monthly, or quarterly. The frequency that data extracts are needed in the data warehouse is determined by the shortest frequency requested through an order, or by the frequency required to maintain consistency of the other associated data types in the source data warehouse.

The standard expectations of a particular source data warehouse for data extracts from the operational database system of record. A system of record uses an extract specification to retrieve a snapshot of shared data and formats the data in the way specified for updating the data in the source data warehouse. An extract specification also contains extract frequency rules for use by the data access environment.

Retrieving data from a source system for process or analysis.

Software that reads one or more sources of data and creates a new image of the data. See also extract-transform-load (ETL).

An architectural approach integrating data management capabilities across platforms.

A method of transparently joining or linking data from multiple physical locations and/or multiple platforms.

The transfer of data between systems, applications, or datasets.

A visual representation of how data moves or is moved between logical processes or application services (i.e., how the output data from a process serves as the input data for other processes). Essentially a process model, complementary to a data model. Defines the requirements and master blueprint for storage and processing across databases, applications, platforms, and networks.

The exercise of authority, control, and shared decision-making (planning, monitoring, and enforcement) over the management of data assets. See governance; data stewardship.

The highest-tier data governance organization in an enterprise. The DGC includes senior managers serving as executive data stewards, along with the data management leader and the CIO. A business executive may formally chair the council as chief data steward with the data management leader serving as facilitator for council meetings and other activities.

A staff organization of full-time data analysts found in larger enterprises whose mission is to support the data governance council, data stewardship coordinating committees, and data stewardship teams.

The level of detail represented in a dataset.

Aligning data definitions, formats, and values across systems.

Applying a hash function to transform data into a fixed-size value.

The process of restricting access to data based on concerns regarding proprietary content, economic impact, security implications.

The data that have been identified thus far for potential inclusion in the information system. The process of specifying which data should or will be sought to fulfill user needs. A description of the different types of data and their applicable tools for analysis is also included.

Data that is stored in a distributed network of systems, where the location of the data is unknown and transparent to the user

Data that is carried across networks between systems.

The ability to change the logical or physical structure of data without changing the application program and its view of the data.

On a large scale, the independence of the data architecture from the business activity architecture, the platform architecture, and the information system architecture. On a smaller scale, the independence of the logical design from the physical platform where data will be stored.

1. A single piece of digital information.

2. A specific set of data values for the characteristics in a data occurrence that is valid at a point in time.

3. One data instance is the current instance and the others are historical or for a period of time. Many data instances can exist for each data occurrence, particularly when historical data are instances.

The movement and consolidation of data within and between data stores, applications, and organizations.

An IT professional responsible for data integration processes, practices and software programs across an enterprise.

Part of a master plan for how data is selected, transformed and flows across databases; an important part of enterprise data architecture. It may include database architecture, master data management architecture, business intelligence architecture, and metadata architecture.

A software developer responsible for data integration programming.

Data that complies with all rules regarding definitions, relationships, lineage, and heritage.

In data movement, data that is provably not changed unexpectedly through transmission between systems.

A role in which individuals transform data from one form, not created by them, into another form. For example, a data entry clerk enters data from a paper form into a database.

The ability for multiple systems to communicate with one another.

A comprehensive list of all data objects in a system or an organization, including electronically stored data such as databases and files, and nonelectronic data.

Keeping data segregated for security or operational purposes.

A defect or anomaly affecting data quality or usability.

A string representing a variable value that is used in encryption.

A large storage repository for structured and unstructured data.

Data management architecture that combines data lakes with data warehouses.

The time delay for data to be updated in a system compared to the real world. When data is displayed in real time, data latency is eliminated.

A conceptualization of how data is created and used which attempts to define a “birth-to-death” value chain for data, including acquisition, processing, analysis, storage and maintenance, archiving and retention, and disposal or destruction.

A visual representation of data’s lifecycle.

Ability to read, understand and communicate data insights.

The process of populating more than one row at time into database, typically a data warehouse.

The business function that develops and executes plans, policies, practices, and projects that acquire, control, protect, deliver, and enhance the value of data.

A program for implementation and performance of the data management function.

The field of disciplines required to perform the data management function.

The profession of individuals who perform data management disciplines.

In some cases, a synonym for a data management services organization that performs data management activities.

See DAMA International.

See Body of Knowledge, Data Management (DAMA-DMBOK®).

See center of excellence, data management.

All the data management professionals, data stewards, and other stakeholders with an active interest and role in data management.

One of the business processes within data management.

A generic term used for the highest-level manager of data management services organizations; the manager most directly responsible for data management, including coordinating data governance and data stewardship activity, overseeing data management projects, and supervising data management professionals.

A centralized data management organization performing data management functions; one or more units of data management professionals responsible for data management within an organization. A centralized data management services organization is sometimes known as a data management center of excellence.

Selected courses of actions setting the direction for data management within the enterprise, including vision, mission, goals, principles, policies, and projects.

See chart, data map.

The assignment of source data entities and attributes to target data entities and attributes, and the resolution of disparate data.

A term used for classifying data at a deep meaningful level for its sensitivity (secret, etc.) and appropriate release. For example, some data will not be sensitive on its own, but will not be releasable to certain countries, or in combination with other data, which then makes it sensitive. Classification and security considerations often shape how markings are applied.

A decision-support database supporting business intelligence in a limited subject area, using a dimensional data model design. Typically, data marts source their data from an enterprise data warehouse or operational data store.

See mashup, data.

A method for creating a version of data by obscuring individual items within a database. Used to make the data anonymous. Typically used for development or testing.

A decentralized data architecture that organizes data by a specific business domain. It helps scale analytics adoption beyond a single platform and a single implementation team.

An architecture that enforces data security policies within and between domains to provide centralized monitoring of data sharing functions. It enables domain teams to perform cross domain analysis with operational and analytical data models as data products.

A central data management framework that governs and records the data available in an organization. A data mesh model prevents data silos from forming within specific business domain systems.

The process of transferring data from one database to another. See also conversion.

The process of sifting through large amounts of data using pattern recognition, fuzzy logic, and other knowledge discovery statistical techniques to identify previously unknown, unsuspected, and potentially meaningful data content relationships and trends. See also predictive analysis.

A model that includes formal data names, comprehensive data definitions, proper data structures, and precise data integrity rules. A complete data model must include all four of these components.

The visual presentation of the structural portion of a data model with icons for entity records and lines between them to represent relationships. See also data structure diagram.

A data model that is presented at a high level of abstraction, hiding the underlying details, and making it easier for people to comprehend. A conceptual model should reflect the way the users think. For example, many-to-many relationships are common in conceptual models.

A data model that represents data in a star-like structure of only one-to-many relationships, where each entity has either all relationships having the “one” side or the “many” side. See also schema, star.

A conceptual data model or logical data model providing a common consistent view of shared data across the enterprise, however that is defined, at a point in time. It is common to use the term to mean a high-level, simplified data model, but that is a question of abstraction for presentation. See also data model, conceptual (CDM).

A data model that represents data in a tree-like structure of only one-to-many relationships, where each entity may have a “many” side when related to a parent, and a “one” side when related to a child. See also structure, hierarchical.

An entity-relationship data model including data attributes that represent the inherent properties of the data, including names, definitions, structure, and integrity rules, independent of software, hardware, volumetrics, frequency of use, or performance considerations.

A representation of objects and their participation in one or more owner-member sets. In such a model, a both owners and members may participate in multiple sets, affecting a network of objects and relationships.

The definition or representation of a data model for implementation and realization in a particular database management system, including naming convention and physical data types. It may be denormalized for performance and access simplification. A high-level description of a database design without specific physical layout (how the data is stored on disk) information.

A conceptual data model that provides structure and defines meaning for non-tabular data, making that meaning explicit enough that a human or software agent can reason about it. See also ontology.

A person who builds data models.

An analysis and design method, building data models to

• define and analyze data requirements,
• design logical and physical data structures that support these requirements, and
• define business metadata and technical metadata.

The act of creating a data model.

A conventional system of symbols for modeling data.

One of several notation conventions for modeling data, developed by Richard Barker and others in 1986.

The formalism, technique, style, notation, etc. used to guide the data modeling activity to create a data model. The scheme encompasses the notational conventions (syntax) for representing the semantics of the data model. Examples of data modeling schemes include single file, flat file, multi-file, relational, hierarchical, record-based, ER, EER, fact oriented (no file), IE, UML, IDEF1X, Barker, multidimensional, star, and object-oriented.

A data modeling scheme that is not record-based – it does not use the constructs of file or entity tables, and consequently does not suffer from table think. See also fact-oriented modeling; object–role model.

A data modeling scheme in which records are formed by clustering attributes. Used to represent an entity type population. One or more attributes may serve as an identifier. In general, a record could have a hierarchical structure, thus allowing multi-valued data items and repeating groups of items.

A data modeling scheme that uses the constructs of entity, attribute, identifier, and foreign key to represent relationships. Attributes are represented by data items or columns. Entities are represented by tables, which is a cluster of one or more attributes. Relationships between entities are represented by foreign keys. The major distinguishing characteristic of a relational data model is that all attributes must be single valued (atomic). See also flat file.

The process by which businesses earn revenue from their data assets.

The process of extracting data from one system and loading it onto another system. See also extract-transform-load (ETL).

The process that brings data into a normal form that minimizes redundancies and keeps anomalies from entering the data resource. It provides a subject-oriented data resource based on business objects and events.

The frequency with which a particular, event, value, or behavior appears within a given dataset or time period; most often used to identify patterns, trends, and relationships in data.

A deluge of data coming at a recipient that is not relevant and timely. An overabundance of unwanted noninformation.

An individual responsible for definitions, policy, and practice decisions about data within their area of responsibility. For business data, the individual may be called a business owner of the data.

Assignment of accountability for data assets.

Processes moving and transforming data between systems.

Short statements of management intent and fundamental rules governing the creation, acquisition, integrity, security, quality, and use of data and information.

The process that involves checking or logging the data in; checking the data for accuracy; entering the data into the computer; transforming the data; and developing and documenting a database structure that integrates the various measures. This process includes preparation and assignment of appropriate metadata to describe the product in human-readable code or format.

The degree to which information products (reports, screens, charts) are easy to understand and use without misinterpretation by the intended audience.

The limitation of data access to only those authorized to view the data. See also confidentiality.

The operation performed on data, through capture, transformation, and storage, in order to derive new information according to a given set of rules.

A person, organization, or software service creating or providing data. See also data creator.

A collection of statistics about a data attribute that shows patterns of usage, patterns of contents, and any other patterns that may be of interest.

Someone who performs data profiling.

An approach to data quality analysis, using statistics to show patterns of usage and patterns of contents, and automated as much as possible. Some profiling activities must be done manually, but most can be automated.

The distribution of data from one or more source databases to one or more local target databases, according to defined rules. Typically used in reference to distributed databases. See also data replication.

Information about the origin of an organization’s data.

The degree to which data is accurate, complete, timely, consistent with all requirements and business rules, and relevant for a given use. See also information quality (IQ).

The evaluation of data quality; the identification of inaccurate, incomplete, inconsistent, and untimely data and its causes.

See data quality audit.

Quality inspection and review processes for data, data models, and database designs, including testing for application data controls and edits, testing of data integration programs, data quality analysis, and data quality audits. See also quality assurance (QA).

The random sampling of data and testing it against its valid data values to determine its accuracy and reliability.

A declaration that a database has met a set of defined data quality requirements (service levels), based on data quality analysis and audits.

The rate that a data attribute loses accuracy over time if not updated. For example, if age of individuals is stored, the entire dataset’s age attribute will be incorrect after one year because everyone will have aged by then.

The application of total quality management concepts and practices to improve data and information quality, including setting data quality policies and guidelines, data quality measurement (including data quality auditing and certification), data quality analysis, data cleansing and correction, data quality process improvement, and data quality education.

System analysis and redesign to eliminate or prevent data errors and defects. A proactive, preventive approach to improving data quality.

Application requirements that eliminate or prevent data errors, including requirements for domain control, referential integrity constraints, and edit and validation routines.

The process of adjusting data derived from two different sources to remove, or at least reduce, the impact of differences identified.

A physical grouping of data items that are stored in or retrieved from a data file. It is referred to as a row or tuple in a relational database. A data record represents a data instance.

The storing of the same data in multiple places, either intentionally (for backup) or unintentionally (leading to inconsistent data).

The unknown and unmanaged duplication of business facts.

The process of analyzing, standardizing, and transforming data from nonstandard files and databases into a standardized database that is part of the enterprise data architecture.

The process of applying updates as a group to a dataset, then allowing users access to the updated data.

Relates two data table objects to each other through data column objects.

The residue of data that has been nominally erased or removed.

The consistent copying of data from one primary data site to one or more secondary data sites. The copied data is kept in synch with the primary data on a regular basis.

Statements describing the data needs of a person or organization. Business metadata (data names and meanings) and logical data models are structured ways of defining data requirements, in addition to more traditional requirement specifications.

See data management (DM).

Rules defining how long data is stored and when it is to be disposed.

Potential negative impact from data misuse or failure.

See data cleansing.

The safety of data from unauthorized and inappropriate access or change.

The measures taken to prevent unauthorized access, use, modification, or destruction of data.

Testing of data security measures by an objective party.

The process of ensuring that data is safe from unauthorized and inappropriate access or change. Includes focus on data privacy, confidentiality, access, functional capabilities, and use.

An interface to a business process that receives or delivers data attributes, usually via a web application.

Exchange of data and/or metadata in a situation involving the use of open, freely available data formats, in which process patterns are known and standard, and the exchange is not limited by privacy and confidentiality regulations.

An agreement between parties that describes the allowed activities, uses, and restrictions regarding data shared between the parties.

A collection or repository of data that is controlled by one department or business unit and not easily accessible by the rest of the organization.

Origin from which data is collected.

Connection information for a database used in an Open Database Connectivity connection setup.

The process of moving data from one system into intermediate storage before final processing into a target.

A database that stands between the operational source databases and the target databases (typically an operational data store, data warehouse, or data mart). The data staging area is considered the “back room” portion of the data warehouse environment. It is where the extract, transform, and load effort takes place, and is out of bounds for end users. Most data in the data staging area is transient, although typically there is some relatively small amount of persistent data.

The agreed-upon format or definition for data elements.

A business leader and/or subject matter expert designated as accountable for:

• the identification of operational and business intelligence data requirements within an assigned subject area;
• the quality of data names, business definitions, data integrity rules, and domain values within an assigned subject area;
• compliance with regulatory requirements and conformance to internal data policies and data standards;
• application of appropriate security controls;
• analyzing and improving data quality; and
• identifying and resolving data-related issues.

Data stewards are often categorized as executive data stewards, business data stewards or coordinating data stewards. See also data owner; data stewardship; data governance.

Formal, specifically assigned, and entrusted accountability for business (nontechnical) responsibilities ensuring effective control and use of data and information resources. See also data steward; stewardship; data governance.

Formal accountability for business responsibilities ensuring effective control and use of data assets.

A permanent cross-functional group of coordinating data stewards responsible for

• supporting the data governance council, and
• integrating the work of data stewardship teams.

The data governance council may delegate responsibilities to the DSC. The DSC may be led by the chief data steward, data management leader, and/or the enterprise data architect. A large organization may have additional DSCs at one or more levels lower than the enterprise DSC.

A generic term for any committee of data stewards. May be synonymous with data governance council (DGC), with both executive data stewards and coordinating data stewards, or may be a working committee of coordinating data stewards below the DGC.

A temporary or permanent focused group of business data stewards collaborating on data modeling, specification, and data quality improvement, typically in an assigned subject area, led by a coordinating data steward and facilitated by a data architect.

The means of recording or archiving data so that it is available for future use.

A place where data is stored; data at rest. A generic term that includes databases, flat files, and nonelectronic data files.

A business plan for leveraging an enterprise’s data assets to maximum advantage. See also enterprise data strategy.

Continuous flow of data, often real-time data.

A set of structural metadata associated to a dataset, which includes information about how concepts are associated with the measures, dimensions, and attributes of a data structure along with information about the representation of data and related descriptive metadata.

The visual presentation of a data model with icons for entities with attributes and lines between them to represent relationships and roles. First known published article to propose such diagrams was by Charles Bachman in 1969. See also data model diagram; entity-relationship diagram (ERD).

A person, place, thing, concept, or event that is of interest to the organization and about which data is captured and maintained in the organization’s data resource.

The flow of data across business processes.

An unmanaged data lake that is either inaccessible to intended users or provides little value. Data swamps occur when there is little data governance and/or proper planning.

The continuous harmonization of data attribute values between two or more different systems, with the end result being that data attribute values are the same in all of the systems.

The process of combining and evaluating data from different sources. The aim is to identify patterns and relationships in the data for analysis.

The evaluation, selection, implementation, inventory, and maintenance of hardware and software products in support of data management, including database management systems, data modeling and database administration tools, metadata management tools, data integration tools, and business intelligence tools.

The process of moving data from one system or operating environment to another.

Changing the format, structure, integrity, and/or definitions of data from the source database to comply with the requirements of a target database.

The mechanism that moves data from a source to a target environment.

A category of physical data structures with common physical properties and uses, such as numeric, alphanumeric, packed decimal, floating point, and datetime.

A set of distinct values characterized by properties of those values and by operations on those values.

The process of inserting or modifying a data attribute in a database.

The process of monitoring the results of data compilation and ensuring the quality of the computational results.

The process of evaluating stored data against established acceptance criteria to determine its quality and usability.

The specific representation of a value for an attribute as of a point in time.

The flow of data across processes in support of the enterprise’s business value chain.

The identification of which functions, processes, applications, organizations, and roles create, read, update, and delete (CRUD) different kinds of data (subject areas, entities, attributes), expressed in CRUD matrices, particularly when the compared items are arranged in value chain sequence.

A concept, originated by Dan Linstedt, that organizes data for decision support into hubs, links, and satellites. This method supports rapid and flexible loading of warehouse data.

Managing changes to datasets over time. The process of identifying and ordering snapshots of data as it changes over time according to certain criteria. Each version becomes an independent instance.

Accessing data without physical movement.

Techniques for graphical representation of trends, patterns, and other information.

The amount of data stored or processed.

An integrated, centralized decision-support database and the related software programs used to collect, cleanse, transform, and store data from a variety of operational sources to support business intelligence. A data warehouse may also include dependent data marts.

A subject-oriented, integrated, time-variant, and nonvolatile collection of summary and detailed historical data used to support the strategic decision-making processes for the corporation.

A copy of transaction data specifically structured for query and analysis.

A system containing integrated servers, storage, and software specifically optimized for data warehouse processing.

See architecture, business intelligence.

A collection of checks and balances to ensure the right data is extracted from the right sources, then transformed, cleansed, and summarized correctly, and finally loaded to the right target database tables.

A relational database management system or multidimensional database management system. Data warehouse engines require strong query capabilities, fast load mechanisms, and large storage requirements.

See infrastructure, data warehouse.

An integrated network of data warehouses that contain sharable data propagated from a source data warehouse based on information consumer demand. The warehouses are managed to control data redundancy and to promote effective use of the sharable data.

Implementation of a data warehouse that enables real-time or near-time data analysis.

A conceptual data warehouse made up of multiple decision-support databases, potentially on multiple servers, but presented transparently to business intelligence users as a unified schema for query, analysis, and reporting.

An enterprise data warehouse fed by extracts from departmental data warehouses and/or legacy data warehouses prior to their incorporation and/or retirement.

A data warehouse that draws data from nearby operational systems and supports a distinct organization, functional area (such as manufacturing), or geographic unit within the enterprise. Distinct from an enterprise data warehouse.

The operational extract, cleansing, transformation, and load processes, and associated control processes, that maintain the data containing within a data warehouse.

The storage of data for the analysis of trends and patterns in the business.

The operational, administrative, and control processes that provide access to business intelligence data and support to knowledge workers engaged in reporting, query, and analysis.

Preparing raw data for analysis.

A US government website launched by the federal chief information officer of the United States in order to make government-collected data available for use by the public.

An organized collection of data stored in a structured way to enable rapid search and retrieval by a computer.

A common application programming interface used to call database functions to allow an application to connect to multiple different databases without function calls for all possible databases.

A database structure that serializes values by columns and then by rows, rather than conventional databases, which serialize values by rows and then by columns.

A database management system that stores content by column rather than by row.

A database management system that is data model independent and designed to efficiently handle unplanned, ad hoc queries in an analytical system environment. Unlike relational database management systems (records-based storage) or column-oriented databases (column-based storage), a correlation database uses a value-based storage architecture in which each unique data value is stored only once and an auto-generated indexing system maintains the context for all values.

A database that contains objects residing on independent systems in a network, but can be accessed as though all objects reside on the same system.

A database in which all relationships among data entities and attributes are hierarchical (see relationship, hierarchical). Sometimes used to refer to databases that have hierarchical record structures but allow more general network relationships between record types. Examples include UML, most object-oriented data models, Kroenke’s Semantic Object Model, the SQL:99 standard (and later versions), and nested relations. See also structure, hierarchical.

A database that provides a historical perspective on the data; that is, a database that can be used to show how facts about an entity have changed over time.

A data structure with three or more independent dimensions.

A type of database in which records are stored with links or pointers to other records. Distinguished from a hierarchical database in the sense that a child record may have relationships with multiple parent records.

A database based on the object-oriented paradigm instead of the relational model.

A database supporting one or more transactional applications. Operational databases are the sources of data for operational data stores and data warehouses. They contain detailed data used to run the day-to-day operations of the business. The data continually changes as updates are made. See also online transaction processing (OLTP).

The most common form of database, storing data in tables made of up of columns and rows, with primary keys, created using the relational data modeling scheme.

A database that feeds into a target database. May be an operational database, operational data store, data staging area, or data warehouse.

The database in which data will be loaded or inserted.

A database with built-in time aspects, including valid time and transaction time.

The function of managing the physical aspects of data resources, including database design and integrity, backup and recovery, performance and tuning, generally within the context of a particular database management system.

The professional role responsible for designing, maintaining, securing, and operating databases to ensure that data is correctly stored and retrieved.

A database administrator (DBA) who supports application systems, sometimes focusing on development and test environments, database design, and SQL tuning as opposed to the entire application stack. Contrasts with operational DBA and procedural DBA.

A database administrator (DBA) focused on support of production environments, including performance tuning, backup and recovery, high availability, job scheduling, data delivery, and security access levels. The operational DBA has a specific responsibility for change management regarding implementation.

A database administrator (DBA) who specializes in development and support of procedural logic controlled and executed by the database management system: stored procedures, triggers, and user-defined functions.

A database administrator (DBA) who supports the development of data management applications.

The logging, monitoring, analysis, and reporting of database activity.

See schema, database.

The process of developing a physical data model, followed by definition of all physical database objects, including tables, indexes, and sequences.

The physical data model and the detailed data definition language for a database. The database design addresses physical constraints such as storage and performance.

See data modeler.

The degree to which data in a database conforms to logical integrity constraints through the implementation of physical database management system constraints.

The degree to which data in a database can be recovered in the event of a hardware or software failure.

A comprehensive list of all databases within a system or an organization.

The development and support of structured data resources. Database management is broader in scope than database administration, including responsibilities beyond those of database administrators.