D

DAMA Foundation, The

The Research and Education Affiliate of DAMA International with a mission to promote development of a formal, certified, recognized, and respected data management profession. Currently supporting this effort through publication of the DAMA Dictionary and DAMA-DMBOK.

DAMA International

An international not-for-profit association of data resource management professionals with chapters and members-at-large around the world, dedicated to advancing the concepts and practices of managing data, information and knowledge as enterprise assets. DAMA International is the leading data management professional organization worldwide.

DAMA-DMBOK Functional Framework

The organizing structure for the DAMA-DMBOK Guide, consisting of a functional decomposition of ten data management functions mapped against seven environmental elements (Goals & Principles, Activities, Deliverables, Roles & Responsibilities, Practices & Techniques, Technology, and Organization & Culture). (DAMA-DMBOK GUIDE 1st edition, pg. 12)

DAMA-DMBOK Guide

A document distributed by DAMA International, intended to be a “definitive introduction” to the Data Management Body of Knowledge.

dashboard

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.

data

1. Facts represented as text, numbers, graphics, images, sound, or video. Data is the raw material used to represent information, or from which information can be derived. (Everest 2010)
2. The individual facts that are out of context, and have no meaning by themselves. They are often referred to as raw data, such as 123.45. Data have historically been defined as plural; datum is the singular form. (Brackett 2011)
3. “The digital shadow of haphazard events indifferently recorded.” (Terry Hanold)

data acceptance

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

data accuracy

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.

data acquisition

1. 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.
2. The activity performed to obtain data, or have access to it under either limited or unlimited rights for use.

Data Administration (DA)

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

Data Administrator (DA)

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.

data analysis

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

data analyst

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

data appliance

1. A combination of hardware, software, Database Management System, and storage, all under one umbrella; a “black box” that yields high performance in both speed and storage and makes data access simpler.
2. 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. (DAMA-DMBOK 1st edition pg. 35)

Data Architect (DA)

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.

data architecture

SEE architecture, data.

data architecture management

Defining the blueprint for managing data resources.

data architecture quality

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

data architecture, analysis, and design

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). Previous name of one of the ten data management functions identified in the DAMA-DMBOK Functional Framework.

data architecture, enterprise

1. 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. Enterprise data architecture typically consists of
   a) an enterprise data model (contextual/subject area, conceptual or logical),

   b) state transition diagrams depicting the lifecycle of major entities,

   c) a robust information value chain analysis identifying data stakeholder roles, organizations, processes and applications, and

   d) data integration architecture identifying how data will flow between applications and databases.
2. The data integration architecture may divide into database architecture, Master Data Management architecture, Data Warehouse/Business Intelligence architecture, and meta-data architecture. Some enterprises also include
   a) lists of controlled domain values (code sets), and

   b) the responsibility assignments of data stewards to subject areas, entities, and code sets.
3. The enterprise data architecture is an important part of the larger enterprise architecture that includes business, process and technology architecture.
4. The “data” column of the Zachman Framework for Enterprise Architecture identifies six different classes of design artifacts, each representing a different level of abstraction:
   · Row 1: Objectives/Scope (contextual) – Planner View: a list of subject areas and/or entities important to the business (may be a class hierarchy identifying supertype/subtype inheritance between entities).

   · Row 2: Enterprise Model (conceptual) – Owner View: a conceptual data model showing the business relationships between entities.

   · Row 3: System Model (logical) – Designer View: a logical data model (a fully attributed and normalized logical data model).

   · Row 4: Technology Model (physical) – Builder View: a physical data model (tables, columns).

   · Row 5: Detailed Representations (out-of-context) – Sub-contractor View: data definitions (DDL).

   · Row 6: Functioning Enterprise: the actual data as stored in implemented databases.

data archival

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.

Data As A Service (DAAS)

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

data assimilation

Most prevalently used in geosciences, this is 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 attribute

1. 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.).
2. A unit of data for which the definition, identification, representation, and permissible values are specified by means of a set of characteristics.
3. A representation of a data characteristic variation in the logical or physical data model. A data attribute may or may not be atomic. SEE ALSO attribute.

data attribute domain

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.

data attribute value

An instance of an attribute type or domain.

data attribute, composite

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

data attribute, derived

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.

data attribute, multi-valued

An attribute or data item which 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 (1:M). (Everest 2010)

data attribute, type 1

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

data attribute, type 2

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.

data attribute, type 3

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.

data capture

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

data cardinality

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 x 9 - 1 = 8 possibilities (0:0 is not a valid option).

data certification

The process of verifying and stating that a data set's contents meets expected standards. SEE ALSO certification.

data chaos

A state where multiple redundant, inconsistent databases contain the same data attribute used for a similar purpose, rated by the maximum count of instances of a single data attribute.

data characteristic

An individual fact that describes or characterizes a data subject. It represents a business feature and contains a single fact, or related facts, about a data subject. (Brackett 2011)

data characteristic substitution

An indication that any data characteristic variation can be used for a data characteristic, such as “Date”, can mean any form of a date. (Brackett 2011)

data checking

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

data cleansing

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

data clustering

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).

data compilation

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

data completeness

The degree to which data is captured.

data completeness, fact

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

data completeness, value

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

data compression

1. Algorithms or techniques that change data to a smaller physical size that contains the same information.
2. The process of changing data to be stored in a smaller physical or logical space.

data consistency

The degree to which one set of attribute values match 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). (DAMA-DMBOK GUIDE 1st edition, pg. 296.)

data consumer

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.

Data Control Language (DCL)

A subset of Structured Query Language used to define data security, user function permissions, and data access to data in relational tables.

data conversion

1. The process of changing data structure, format, or contents to comply with some rule or measurement requirement.
2. The process of changing data contents stored in one system so that it can be stored in another system, or used by an application.

data creator

A person who enters or updates data. Roughly equivalent to data producer. SEE ALSO Create-Read-Update-Delete.

data cube

A multi-dimensional 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 OLAP. SEE ALSO schema, star.

data currentness

A measure of how well the data values remain current with the business. (Brackett 2011)

data custodian

SEE data steward.

data definition

1. Statements that specify the business meaning associated with a conceptual, logical, or physical data entity or attribute.
2. The process of creating business meta-data, including names, meanings, integrity rules, and domain values.
3. 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.

Data Definition Language (DDL)

1. Generally, the subset of Structured Query Language commands used to define and implement structured database objects.
2. In Database Management Systems, the specific definitions to formally define and implement a database.

data definition quality

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

data denormalization

The process that adjusts the normalized data structure for optimum performance in a specific operating environment, without compromising the normalized data structure. (Brackett 2011)

data de-optimization

The technique that transforms the logical data structure into the deployment data structure for the data sites where the databases will be implemented. It deals with the specific data that will be maintained in different data sites. (Brackett 2011)

data description

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

data design artifact

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

data development

Analysis, design, implementation, testing, deployment, and maintenance of data. (DAMA-DMBOK Guide, 1st edition, pg. 6.)

data dictionary

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

data dictionary, active

An active data dictionary interacts with its software environment to capture and update meta-data in real time.

data dictionary, integrated

An integrated data dictionary serves as a store for meta-data for multiple software tools. SEE ALSO repository.

data dictionary, passive

A passive data dictionary requires batch or user entry and update of meta-data.

data distribution

1. In data storage, the mathematical patterns of data values as they exist within a set.
2. In data networks, the patterns of storage of data within and through various systems and on various platforms or sites.
3. In data movement, transmission of data to one or more locations from a central point.

data domain

A set of allowable values for a data attribute. (Brackett 2011)

data dredging

Alternate form: data fishing, data snooping

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.

data editing

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.

data element

SEE data attribute.

Data Encryption Standard (DES)

An encryption program. SEE ALSO encryption.

data entity

A classification of objects found in the real world described by the Noun part of speech -- persons, places, things, concepts, and events – of interest to the enterprise. Usually expressed in singular form.

data entity, associative

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

data entity, dependent

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

data entity-relation diagram

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. (Brackett 2011)

data error

A data value that provides incorrect or false knowledge about the business, or about business objects and events that are important to the business. (Brackett 2011)

data escrow

In Software-as-a-Service, the practice of keeping a set of data with an independent third party to prevent data loss.

data exchange

The process of sending and receiving data.

data exploration

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

data export

1. The process of extracting information from a database into a file.
2. The result data set from the export process.

data extract

1. A snapshot copy of data from a source database used to update data in a target database, or for use in an application.
2. Verb. To copy data from a source for data movement and data transformation.

data extract date

The date data was extracted from a source database.

data extract frequency

The latency of data extracts, such as daily versus weekly, monthly, quarterly, etc. 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.

data extract specification

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.

data extraction software

Software that reads one or more sources of data and creates a new image of the data. SEE ALSO Extract-Transform-Load.

data federation

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

data file

A physical file of data that exists in a Database Management System, such as a computer file, or outside a database management system, such as a manual file. It is referred to as a table in a relational database. A data file generally represents a data entity, subject to adjustments made during formal data denormalization. (Brackett 2011)

data file-relation diagram

A diagram that represents the data files and the relations between those data files in a database. (Brackett 2011)

data flow

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

Data Flow Diagram (DFD)

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.

data governance

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

Data Governance Council (DGC)

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

Data Governance Office (DGO)

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.

data heritage

Documentation of the source of the data and their original meaning at the time of data capture. (Brackett 2011)

data hoarding

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

data identification

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 in a cloud

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

data in context

Individual facts that have meaning and can be readily understood. They are raw facts wrapped with meaning. (Brackett 2011)

data independence

1. The ability to change the logical or physical structure of data without changing the application program and its view of the data.
2. 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.

data instance

A specific set of data values for the characteristics in a data occurrence that is valid at a point in time, or for a period of time. Many data instances can exist for each data occurrence, particularly when historical data are maintained. One data instance is the current instance and the others are historical instances. (Brackett 2011)

data instant

The point in time or the timeframe the data represent in the business world. (Brackett 2011)

data integration

The planned and controlled:

for operational and/or analytical use. Data needs to be accessed and extracted, moved, validated and cleansed, standardized, transformed, and loaded.

data integration architect

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

data integration architecture

A part of a master plan for how data is selected, transformed and flows across databases. The data integration architecture is an important part of enterprise data architecture. It may include database architecture, Master Data Management architecture, Business Intelligence architecture, and meta-data architecture.

data integration developer

A software developer responsible for data integration programming.

data integrity

1. Data that complies with all rules regarding definitions, relationships, lineage, and heritage.
2. In data movement, data that is provably not changed unexpectedly through transmission between systems.

data intermediary

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.

data inventory

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

data item

An individual field in a data record, referred to as a column in a relational database. A data item represents a data attribute, subject to adjustments made during formal data denormalization. (Brackett 2011)

data key

Any data attribute or set of data attributes used to identify a data occurrence within a data entity. (Brackett 2011)

data latency

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.

data lifecycle

A conceptualization of how data is created and used which attempts to define a “birth-to-death” value chain for data, including acquisition, storage and maintenance, use, movement to archive, and destruction. (DAMA-DMBOK Guide, 1st edition, pg. 3.)

data lineage

A description of the pathway from the data source to their current location and the alterations made to the data along that pathway. (Brackett 2011)

data loading

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

Data Management (DM)

1. The business function that develops and executes plans, policies, practices, and projects that acquire, control, protect, deliver, and enhance the value of data.
2. A program for implementation and performance of the data management function.
3. The field of disciplines required to perform the data management function.
4. The profession of individuals who perform data management disciplines.
5. In some cases, a synonym for a Data Management Services organization that performs data management activities.

Data Management Association, The (DAMA)

SEE DAMA International.

Data Management Body of Knowledge (DAMA-DMBOK)

SEE Body of Knowledge, Data Management.

data management center of excellence

SEE Center of Excellence, Data Management.

data management community of interest

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

data management function

One of the ten business processes within data management, according to the functional decomposition in the DAMA-DMBOK Functional Framework:

· Data Governance

· Data Architecture

· Data Development

· Data Operations Management

· Data Security Management

· Data Quality Management

· Reference & Master Data Management

· Data Warehousing & Business Intelligence Management

· Document and Content management

· Meta-data Management

DAMA-DMBOK Guide, 1st edition, pg. 6.)

data management leader

Alternate form: DM Leader

A generic term used in the DAMA-DMBOK Guide for the highest-level manager of Data Management Services organizations. The DM Leader is 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. May be a manager, director, Associate VP, or VP.

data management professional

A professional specializing in one or more data management functions, and may or may not be part of IT organizations.

data management services (DMS)

An organization of data management professionals performing data management functions. One or more units of data management professionals responsible for data management within an organization. A centralized DMS organization is sometimes known as a Data Management Center of Excellence.

data management strategy

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

Data Manipulation Language (DML)

A language used to insert, retrieve, update, delete, and otherwise manipulate data in a database. The SELECT statement in SQL is an example of a retrieval operation. (Everest 2010)

data map

SEE chart, data map.

data mapping

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

data marking

A term used for the 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.

Data Mart (DM)

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.

data mashup

SEE mashup, data.

data migration

The process of transferring data from one database to another. SEE ALSO conversion.

data mining

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.

data model

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. (Brackett 2011)

data model diagram

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.

Data Model, Conceptual (CDM)

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 phenomena in the users' world being modeled as directly as possible, as close to the way the users think. For example, many-to-many relationships are common in conceptual models.

data model, dimensional

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.

Data Model, Enterprise (EDM)

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.

data model, hierarchical

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.

Data Model, Logical (LDM)

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

data model, network

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.

Data Model, Physical (PDM)

The definition or representation of a data model for implementation and realization in a particular DBMS, 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.

Data Model, Semantic (SDM)

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.

data modeler

A person who builds data models.

data modeling

1. An analysis and design method, building data models to
   a) define and analyze data requirements,

   b) design logical and physical data structures that support these requirements, and

   c) define business and technical meta-data.
2. The act of creating a data model.

data modeling notation, Barker

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

data modeling notation, IDEF1X (IDEF1X)

A style of notation for entity relationship diagrams in data models, developed by Robert G. Brown in 1979, and extended by the U. S. Air Force in 1985. The 'X' stands for eXtensions to the original IDEF1 specification, the extensions were due to Dan Appleton. This data modeling scheme is one variant of Entity Relationship modeling. It was originally embodied in ERwin^®, which has since evolved to include additional modeling notations. SEE ALSO Integrated DEFinition.

data modeling notation, Information Engineering (IE)

A record-based data modeling scheme and notation developed by Clive Finkelstein in the 1970s and later popularized by James Martin.

data modeling scheme

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, multi-dimensional, star, object-oriented.

data modeling scheme, no file

A data modeling scheme that is not record-based - does not use the constructs of file or entity tables, and consequently does not suffer from table think. (Everest 2010) SEE ALSO Fact Oriented Modeling; object role model.

data modeling scheme, record-based

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. (Everest 2010)

data modeling scheme, relational

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.

data movement

The process of extracting data from one system and loading it onto another system. SEE ALSO Extract-Transform-Load.

data name

A label for a fact or a set of related facts contained in the data resource, appearing on a data model, or displayed on screens, reports, or documents. (Brackett 2011)

data name abbreviation

The shortening of a primary data name to meet some length restriction. (Brackett 2011)

data normalization

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. (Brackett 2011)

data occurrence

A logical record that represents the existence of a business object or the happening of a business event in the business world, such as an employee, a vehicle, and so on. (Brackett 2011)

data operations management

Providing support from data acquisition to purging. (DAMA-DMBOK Guide, 1st edition, pg. 6.)

data overload

A deluge of data coming at a recipient that is not relevant and timely. It is a deluge of unwanted non-information.

data owner

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.

data policy

Short statements of management intent and fundamental rules governing the creation, acquisition, integrity, security, quality, and use of data and information. (DAMA-DMBOK Guide, 1st edition, pg. 47.)

data preparation

The process which 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/format.

data presentation quality

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

data privacy

The limitation of data access to only those authorized to view the data. SEE ALSO confidentiality.

data processing

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

data producer

A person, organization, or software service creating or providing data. SEE ALSO data creator.

data professional

SEE data management professional.

data profile

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

data profiler

Someone who performs data profiling.

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.

data propagation

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.

data provenance

Provenance applied to the organization's data resource. (Brackett 2011)

data quality

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.

data quality analysis

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

data quality assessment

SEE data quality audit; quality assessment.

data quality assurance

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.

data quality audit

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

data quality certification

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

data quality decay rate

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

data quality management

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. One of the ten data management functions identified in the DAMA-DMBOK Functional Framework.

data quality process improvement

System analysis and redesign to eliminate or prevent data errors and defects. Data quality process improvement is a proactive, preventive approach to improving data quality.

data quality requirement

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

data reconciliation

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

data record

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. (Brackett 2011)

data redundancy

The unknown and unmanaged duplication of business facts.

data re-engineering

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

data reference set

A specific set of data codes for a general topic, such as a set of management level codes in an organization. (Brackett 2011)

data refresh

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

data relation

An association between data occurrences in different data subjects or within the same data subject. It provides the connections between data subjects for building the proper data structure and for navigating in the database. (Brackett 2011)

data remanence

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

data replication

The consistent copying of data from one primary data site to one or more secondary data sites. The copied data are kept in synch with the primary data on a regular basis. (Brackett 2011)

data repository

A loose term for a collection of multiple databases. Something entirely different from a meta-data repository. Not recommended for use.

data requirement

Statements describing the data needs of a person or organization. Business meta-data (data names and meanings) and Logical Data Models are structured ways of defining data requirements, in addition to more traditional requirement specifications.

Data Resource Management (DRM)

SEE data management.

data rule

A subset of business rules that deals with the data column of the Zachman Framework. (Brackett 2011)

data scrubbing

SEE data cleansing.

data security

1. The safety of data from unauthorized and inappropriate access or change.
2. The measures taken to prevent unauthorized access, use, modification, or destruction of data.

data security audit

Testing of data security measures by an objective party.

data security management

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. One of the ten data management functions identified in the DAMA-DMBOK Functional Framework. (DAMA-DMBOK Guide, 1st edition, pg. 6.)

data service

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

data set

Any organized collection of data.

data sharing

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

data sharing agreement

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

Data Source Name (DSN)

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

data staging

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

data staging area

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. The data staging area 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.

data steward

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

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

data stewardship

1. The formal, specifically assigned, and entrusted accountability for business (non-technical) responsibilities ensuring effective control and use of data and information resources. SEE ALSO data steward; stewardship; data governance.
2. The formal accountability for business responsibilities ensuring effective control and use of data assets. (DAMA-DMBOK Guide, 1st edition, pg. 39.)

Data Stewardship Committee (DSC)

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

The Data Governance Council may delegate responsibilities to the Data Stewardship Committee. The DSC may be led by the Chief Data Steward, DM Leader, and/or the Enterprise Data Architect. In a large organization, there may be additional Data Stewardship Committees at one more levels lower than the enterprise DSC.

data stewardship council

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.

data stewardship team

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.

data storage

The means of recording or archiving data so that they are available for future use.

data store

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

data strategy

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

data structure definition

A set of structural meta-data associated to a data set, 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 meta-data.

data structure diagram

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 (1969). (Everest 2010) SEE ALSO data model diagram; entity-relationship diagram.

data subject

A person, place, thing, concept, or event that is of interest to the organization and about which data are captured and maintained in the organization's data resource. Data subjects are defined from business objects and business events, making the data resource subject oriented toward the business. (Brackett 2011)

data supply chain

The flow of data across business processes.

data synchronization

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

data technology management

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, Meta-data Management tools, data integration tools and Business Intelligence tools.

data tracking

The process of documenting data provenance. (Brackett 2011)

data transfer

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

data transformation

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

data transport

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

data type

Alternate form: datatype

1. A category of physical data structures with common physical properties and uses, such as numeric, alphanumeric, packed decimal, floating point, datetime, etc.
2. A set of distinct values characterized by properties of those values and by operations on those values. [ISO/IEC 11404:1996, 4.11]

data update

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

data validation

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

data value

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

data value chain

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

data value chain analysis

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

data versioning

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

data visualization

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

Data Warehouse (DW)

1. 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. (DAMA-DMBOK Guide, 1st edition, pg. 197.)
2. A subject oriented, integrated, time variant, and non-volatile collection of summary and detailed historical data used to support the strategic decision-making processes for the corporation. (“What is a Data Warehouse?” W.H. Inmon, Prism, Volume 1, Number 1, 1995)
3. A copy of transaction data specifically structured for query and analysis. (Ralph Kimball, The Data Warehouse Toolkit, pg. 310.)

data warehouse appliance

A system containing integrated servers, storage, and software specifically optimized for Data Warehouse processing.

data warehouse architecture

SEE architecture, Business Intelligence.

data warehouse audits and controls

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

data warehouse bus architecture

The Data Warehouse Bus Architecture is composed of “a master suite of conformed dimensions” and standardized definitions of facts. [1, P. 156]

data warehouse engine

A Relational DataBase Management System or Multi-Dimensional DataBase Management System. Data Warehouse engines require strong query capabilities, fast load mechanisms, and large storage requirements.

data warehouse infrastructure

SEE infrastructure, data warehouse.

data warehouse network

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.

data warehouse, active

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

data warehouse, federated

1. 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.
2. An Enterprise Data Warehouse fed by extracts from departmental Data Warehouses and/or legacy Data Warehouses prior to their incorporation and/or retirement.

data warehouse, functional

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.

Data Warehousing (DW)

1. The operational extract, cleansing, transformation, and load processes, and associated control processes, that maintain the data containing within a Data Warehouse.
2. The storage of evaluational data for the analysis of trends and patterns in the business. (Brackett 2011)

Data Warehousing and Business Intelligence management

The operational, administrative and control processes that provide access to Business Intelligence data and support to knowledge workers engaged in reporting, query, and analysis. One of ten data management functions identified in the DAMA-DMBOK Functional Framework. (DAMA-DMBOK Guide, 1st edition, pg. 7.)

data, analytical

Subject oriented, integrated, time variant, non-volatile collections of data in support of Business Intelligence activities. SEE ALSO OnLine Analytical Processing.

data, derived

A data set 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, non-tabular

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.

data, operational

Process oriented, non-integrated, time current, volatile collections of data used to support the daily activities of an enterprise. SEE ALSO OnLine Transaction Processing.

data, structured

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, tabular

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

data, unstructured

Any document, file, graphic, image, text, report, form, video, or sound recording that has not been tagged or otherwise structured into rows and columns or records. This term has some inaccurate connotations, as there is usually some structure (for instance, paragraphs and chapters) in these formats.

data.gov

A U.S. government website launched by the Federal Chief Information Officer of the U.S. in order to make available government collected data for use by the public.

data-at-rest

Data that is written to and contained in static storage.

database

Alternate form: data base

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

database administration

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 DBMS.

DataBase Administrator (DBA)

The IT professional role responsible for database administration, usually in the context of a particular DBMS, hence often prefixed with the name of the DBMS, e.g., Oracle DBA. Functional responsibilities vary based on further definitions.

DataBase Administrator, application

A 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.

DataBase Administrator, operational

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

DataBase Administrator, procedural

1. A DBA that specializes in development and support of procedural logic controlled and executed by the DBMS: stored procedures, triggers, and user-defined functions. (DAMA-DMBOK Guide, 1st edition, pg. 149.)
2. A DBA that supports the development of data management applications.

database auditing

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

database definition

SEE schema, database.

database design

1. The process of developing a physical data model, followed by definition of all physical database objects, including tables, indexes, and sequences.
2. The physical data model and the detailed DDL for a database. The database design addresses physical constraints such as storage and performance.

database designer

SEE data modeler.

database integrity

1. The degree to which data in a database conforms to logical integrity constraints through the implementation of physical DBMS constraints.
2. The degree to which data in a database can be recovered in the event of a hardware or software failure.

database inventory

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

database management

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

DataBase Management System (DBMS)

The computer software program used to manage and query a database.

database management system, hierarchical

A type of Database Management System, where parent-child relationships are established between data segments.

DataBase Management System, Multi-Dimensional (MDDBMS)

A specialized Database Management System that supports OnLine Analytical Processing, enabling users to analyze large amounts of data. An MDDBMS captures and presents arrays of data that can be arranged in multiple dimensions.

DataBase Management System, Object-Oriented (OODBMS, ODBMS)

Database software that stores data as objects, instead of storing the data in a relational format, and then instantiating objects in memory.

DataBase Management System, Object Relational (ORDBMS)

An Object Relational DBMS to manage an Object Relational Data Structure, which is a hybrid of OO and Relational.

DataBase Management System, Relational (RDBMS)

Database management software controlling the creation, storage, manipulation, access, and performance of relational databases.

database marketing

The use of information about customers and prospects to strengthen customer relationships by identifying new opportunities and improving customer service. Uses methods for creating, testing, and executing marketing strategies based on analysis of customer data. Includes the mass customization of marketing campaigns to decrease costs, improve response, build customer loyalty, reduce attrition, and increase customer satisfaction.

database reorganization

The process of rearranging physical storage for a database in order to optimize performance.

database schema

SEE schema, database.

database server

In a distributed application architecture, the DBMS software, related data integration and access services and associated hardware supporting access and manipulation of data, separate from application logic and user interfaces.

database transaction

A unit of work; a set of statements to read, create, modify, or delete business data, which the Database Management System must complete performance of all the statements or reverse the changes.

database, archival

An exact copy of a database, along with any specific software necessary for managing that database, saved for purposes of historical research, recovery, or restoration.

database, columnar

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

database, column-oriented

A Database Management System that stores its content by column rather than by row.

database, correlation

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.

database, distributed

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

database, hierarchical

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 OO data models, Kroenke's Semantic Object Model, the SQL:99 standard (and later versions), and nested relations. There is increasing interest in moving away from the restrictions of the relational model, which allow only flat record structures. SEE ALSO structure, hierarchical.

database, historical

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

DataBase, Multi-Dimensional (MDDB)

A data structure with three or more independent dimensions.

database, network

A type of database where 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.

DataBase, Object-Oriented (OODB)

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

database, operational

A database supporting one or more transactional applications. Operational databases are the sources of data for data 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.

database, relational

1. The most common form of database today, storing data in tables made of up of columns and rows, created using the relational data modeling scheme.
2. A database conforming to Codd's rules:

Rule 0: The system must qualify as relational, as a database, and as a management system.

Rule 1: The information rule.

Rule 2: The guaranteed access rule.

Rule 3: Systematic treatment of null values.

Rule 4: Active online catalog based on the relational model.

Rule 5: The comprehensive data sublanguage rule.

Rule 6: The view updating rule.

Rule 7: High-level insert, update, and delete.

Rule 8: Physical data independence.

Rule 9: Logical data independence.

Rule 10: Integrity independence.

Rule 11: Distribution independence.

Rule 12: The non-subversion rule.

database, source

A database that feeds into a target database. May be an operational database, ODS, data staging area or Data Warehouse.

database, target

The database in which data will be loaded or inserted.

database, temporal

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

data-in-motion

Data that is carried across networks between systems.

date

1. A point in time with the granularity of a day.
2. A class word, abbreviated usually to dt.
3. DCMI element in element set Instantiation: a timeframe for an event. SEE ALSO Dublin Core Metadata Initiative.

datum

Historically, has been defined as the singular form of data related to one fact. (Brackett 2011)

deadlock

A scenario where a set of multiple simultaneous actions within a set wait for others within the set to complete and release the resources being held. The waiting processes are “locked out” from the resources held by the other processes. A true deadlock lasts forever, is never resolved.

decision rights

In Data Governance, information about the who, when and how a data-related decision is made.

decision support

SEE Business Intelligence.

Decision Support System (DSS)

An application that uses data to support managerial decisions through ad hoc query, summarization, drill-down analysis, trend analysis, exception identification and “what if” scenario modeling. SEE ALSO Business Intelligence.

decision tree

SEE chart, decision tree.

declarative

Adjective. Describes a type of programming language in which the programmer does not define the flow of control at execution time.

decryption

The process of reversing encryption; decoding back into original format.

deduction

1. The process of reasoning from one state to another, such as from cause to effect, or from general to specific.
2. Subtraction.

deduplication

The process of elimination of redundant copies of data from storage or during a merge of multiple datasets.

default data value

Alternate form: default value

A data value that is automatically assigned when no other data values are selected or applied.

defect

A data value that does not conform to its quality requirements. SEE ALSO error.

defect prevention

Improving systems to eliminate or minimize data errors in a database or information product.

defect rate

The percentage of data that is incorrect, inaccurate, or no longer true. The number of defects found compared to the total number of data values.

Defense Advanced Research Projects Agency (DARPA)

The U.S. federal funding source for development of the semantic web.

Define-Measure-Analyze-Design-Verify (DMADV)

A Six Sigma process improvement method, used for projects to design and create new product or processes.

Define-Measure-Analyze-Improve-Control (DMAIC)

A Six Sigma process improvement method, used for projects to improve existing business processes.

definition

1. A statement conveying a fundamental character or the meaning of a word, phrase, or term. It is a clear, distinct, detailed statement of the precise meaning or significance of something. (Brackett 2011)
2. The process of assigning names, description, and specification.

degenerate dimension

SEE dimension, degenerate.

degenerate fact table

SEE fact table, factless.

degree

The number of attributes (columns) in a record or relation including those making up the identifier. (Everest 2010)

delete

1. To remove or erase.
2. A SQL statement (command) that specifies removal of data in a relational database.

deliverable

An expected output or outcome from a project, function, activity, or task. Usually an information delivery product, such as a document or database.

delta

1. A Greek letter (Δ) signifying the difference between two statistical values.
2. The term used to identify rows that have changed between time periods, used in ETL processing.

delta update

A dataset containing only the data that was updated between the last extraction or snapshot process and the current execution of the extraction or snapshot.

Deming Cycle

The “plan-do-check-act” cycle of continuous improvement developed by Walter Shewhart and popularized by W. Edwards Deming. SEE ALSO Shewhart Cycle.

demographics

A segment of a population delineated by certain shared inherent characteristics.

demography

The study of human populations through statistics.

denormalization

The process of reversing the decomposition resulting from applying the rules of normalization; recombining records. (Everest 2010)

dense index

SEE index, dense.

density-equalizing map

SEE chart, area cartogram.

Department of Defense Architecture Framework (DODAF)

An architecture framework developed by the U.S. Department of Defense in the 1990s.

dependency

Characteristic of a relationship that expresses “must have at least one.” Also called mandatory, required, exhaustive, or NOT NULL. Opposite of optional, orphan, or nullable. (Everest 2010)

dependency, functional

1. In a relationship, a constraint between any two attributes, where one attribute value matches to one and only one value of the other attribute.
2. Used in the context of an attribute in an entity record, an attribute instance cannot exist without being related to an entity instance (the dependency part) and there can be at most one instance (value) for that attribute for each entity instance (the function part where A = fn(X) - given a value for X, fn uniquely determines a value for A. In this case, X is called the determinant of A.).

dependency, multi-valued

In a relationship, a constraint between sets of attributes where the values of one set of attributes match to one and only one other set of attribute values. Contrast with functional dependency where the constraints involve only one attribute from each set.

dependency, partial

A type of dependency in which the value of a non-key field is determined by a part of a composite key, thus violating second Normal form.

dependency, transitive

A type of dependency in which the values of non-key attributes are determined by another non-key attribute, rather than the entity key. It is a functional dependency but between two non-key attributes, hence violating third Normal Form. SEE ALSO dependency, functional.

dependent data mart

A data mart whose tables are sourced from an Enterprise Data Warehouse.

dependent entity

SEE data entity, dependent.

deployment

The act of putting information technology into productive use. Installation puts the system into the production environment. Deployment includes installation, but also includes efforts to train and encourage effective use.

deployment diagram

A visual representation of the configuration of a system deployed in a production environment, including hardware, software, data objects, and all processes that use them, including processes that only exist while executing.

derived attribute

SEE data attribute, derived.

derived data

SEE data, derived.

description

1. A textual representation of a thing.
2. A class word, abbreviated usually to desc.
3. DCMI element in element set Content: a textual, tabular, or graphical portrayal of a resource. SEE ALSO Dublin Core Metadata Initiative.

descriptive meta-data

SEE meta-data, descriptive.

descriptive model

A model that describes how a system actually works.

design

1. A deliberate, purposeful plan, layout, delineation, arrangement, and specification of the component parts and interfaces of a product or system. A logical design is an abstract design for fulfilling requirements without consideration for physical constraints. A physical design considers the requirements along with physical constraints.
2. Verb. To conceive, plan, define, arrange, and specify a product or system.

Design For Six Sigma (DFSS)

SEE Define-Measure-Analyze-Design-Verify.

design review

A process where all aspects of a system design are reviewed publicly before code construction starts.

Desktop OLAP (DOLAP)

SEE OnLine Analytical Processing, Desktop.

determinant

The entity domain that determines the value of an attribute. SEE ALSO dependency, functional.

deterministic matching

A type of matching that relies on defined patterns and rules for assigning weights and scores for determining similarity. (DAMA-DMBOK Guide, 1st edition, pg. 310.)

developer

A person who designs, codes and/or tests software. Different types are known as software developer, systems developer, application developer, software engineer, or application engineer.

development activity

In the DAMA-DMBOK Functional Framework, an activity undertaken with projects and recognized as part of the Systems Development LifeCycle, creating data deliverables through analysis, design, building, testing, and deployment. SEE ALSO activity group.

deviation

The measure of difference between expected and observed values, or more generally, between any two values.

diagram

A visual representation of relationships between multiple things, i.e., how a system works, how parts are related to the whole. SEE ALSO chart.

dialect

A subset of language used or agreed to by a group of people. An ontology defines the precise meaning of the vocabulary in a dialect and the relationship between these terms.

dice

A slice operation on more than two dimensions of a data cube, or more than two consecutive slices. (DAMA-DMBOK Guide, 1st edition, pg. 236.) SEE ALSO slice.

dictionary

A collection of definitions for words, terms, and phrases that differentiate closely related words. SEE ALSO data dictionary.

Digital Elevation Model (DEM)

A digital representation of a topography or terrain, using regular shapes (squares or triangles) to approximate roughness of a surface.

digital preservation

The management of data on digital media over time. As digital media storage mediums and storage applications change, either data must be moved to new media, or old storage retrieval mechanisms and applications must be kept operational.

digital rights management

A generic term for technologies that can be used to impose limitations on usage of digital content and/or devices.

Digital Terrain Model (DTM)

SEE digital elevation model.

digitize

Verb. To convert something into a binary representation for computer storage and/or use.

dimension

1. Generally, an axis from which you can regard or summarize something.
2. In architecture, one of a series of properties that together are used to uniquely identify a location or a component of a system.
3. In Business Intelligence, a category for summarizing or viewing data (e.g., time period, product, product line, geographic area, organization).
4. In dimensional modeling, a type of table, or a structural attribute of a data cube containing a list of members, all of which are of a similar type in the user's perception of the data. For example, all months, quarters, years, etc., make up a time dimension; likewise all cities, regions, countries, etc., make up a geography dimension. A dimension acts as an index for identifying values within a multi-dimensional array. Dimensions offer a very concise, intuitive way of organizing and selecting data for retrieval, exploration, and analysis.

dimension table

In dimensional modeling, a table containing a row for each occurrence of a dimension list, linked to one or more fact tables through use of the dimension table key as a foreign key in each related fact table.

dimension, conformed

A dimension that exists once but is used in multiple star schemas, so that the dimension content and meaning is the same regardless of which fact table is joined.

dimension, degenerate

A dimension where there are no valid dimensional attributes other than a unique identifier in a one-to-one relationship with a fact table.

dimension, junk

A dimension that consists of multiple loosely-related codes and indicators collected into one table in order to reduce the number of keys and indexes needed in a star schema.

dimension, mini

A dimension that includes attributes of another dimension that change over time more frequently than is desired. This sometimes greatly enhances load performance by concentrating the write operations to a small subset of attributes.

dimension, slowly changing

A dimension containing data that changes over time, such that the rate of change is a small percentage of the total row count (i.e., 1% per quarter). Dimensions of type 0, 1, 2, 2A, 3, 4, and 6 are all types of slowly changing dimensions.

dimension, slowly growing

A dimension that slowly increases in the number of rows.

dimension, type 0

A dimension where no updates occur. All rows stay as they were when initially written to the table.

dimension, type 1

A dimension in which all attributes are type 1, so all attributes are overwritten with new data.

dimension, type 2

A dimension in which all attributes are type 2, so any attribute that changes for the business key requires generation of a new row.

dimension, type 2A

Similar to a type 2 dimension, a type 2A writes a new row for any change in the data for the row and is time-date stamped. However, the old row is retired to a history table; it is not left in the current table. So in effect, the type 2A table resembles a type 1 in its contents. However, it can be joined to the history table to get a full type 2 view.

dimension, type 3

A dimension in which all attributes are type 3, so that any attribute that changes for the business key will require copying attribute values to other attributes before the original attributes are overwritten.

dimension, type 4

A dimension table where the data is physically split into two tables, one with the current value rows, and the other with only historical value rows.

dimension, type 6

A dimension table which combines the attributes of types 1, 2 and 3 (1+2+3=6).

dimensional aggregate

A computed value derived from the calculation of a fact measure at the intersection of one or more dimensions at non-granular levels.

dimensional model

A specialized type of physical data model particular to a retrieval-only database design, commonly used in Data Warehouses and data marts, where de-normalized fact tables are linked to dimension tables. Star schemas and snowflake schemas are examples of dimensional models.

direct access file system

A protocol for data access across systems using data files instead of blocks.

Direct Access Storage Device (DASD)

A type of storage device where access is directly to the device, rather than through a cache or other interface.

Direct Attached Storage (DAS)

A storage device attached to a server or workstation without the use of a storage network.

Direct Marketing Association (DMA)

The largest and oldest international trade association that seeks to advance the efficacy of all forms of direct marketing.

directory

1. Generally, information heavily optimized for searching and reading.
2. In data storage, a table, index or folder containing addresses and locations of data or relationships between data objects.
3. In operating systems, a synonym for a folder in Windows and other operating systems, used to organize stored files and other folders.
4. A type of meta-data store that limits the meta-data to the location or source of data in the enterprise. (DAMA-DMBOK 1st edition, pg. 282.)

dirty data

Data with a high degree of inaccuracy, incompleteness, inconsistency, or that fail some edit criteria.

disaggregation

The breakdown of computations usually within a common branch of a hierarchy, to a more detailed level for which detailed measures can be attributed.

disambiguate      

Verb. To clarify the meaning of a term by selecting between alternate interpretations.

disambiguation

The process of identifying attributes to differentiate or clarify between alternate interpretations.

disaster recovery

A protocol and associated execution to recover lost computing-system usage (applications, data, and data transactions) committed up to the moment of system loss.

disparate

Adjective. Fundamentally dissimilar in kind, or containing or including dissimilar or unlike attributes. Opposite of similar.

disparate data

Data that are essentially not alike, or are distinctly different in kind, quality, or character. They are unequal and cannot be readily integrated to meet the business information demand. They are low quality, defective, discordant, ambiguous, heterogeneous data. (Brackett 2011)

distance cartogram

SEE chart, distance cartogram.

distributed database

SEE database, distributed.

Distributed Relational Database Architecture (DRDA)

An IBM architecture for coordinating data across multiple relational Database Management Systems.

document

1. Generally, any information delivery vehicle, paper or electronic.
2. In data management, the content and structure in an electronic file.
3. In document or record management, a paper object in the real world, which may include signatures.

document and content management

Managing data found outside of standard structured databases. One of ten data management functions identified in the DAMA-DMBOK Functional Framework. (DAMA-DMBOK Guide, 1st edition, pg. 7.)

document management

The storage, inventory, and control of electronic and paper documents. (DAMA-DMBOK Guide, 1st edition, pg. 239.)

Document Management System (DMS)

An application used to track and store electronic documents and/or images of paper documents. Document management systems commonly provide storage, versioning, meta-data, and security, as well as indexing and retrieval capabilities.

Document Object Model (DOM)

A platform and language neutral application programming interface that allows programs and scripts to dynamically access nodes in an XML document and update the content, structure and style of these documents.

Document Type Definition (DTD)

A text file that specifies the meaning of each tag.

document, record, and content management

Control over capture, storage, access and use of data stored outside structured databases. An older name for one of ten data management functions identified in the DAMA Functional Framework.

documentation

Descriptive text and images used to define or describe an object, design, specification, instructions, or procedure.

domain

1. Generally, a set of things that have a common definition, such as the set of possible values for an attribute, or the population of an entity.
2. In data modeling, a type of attribute with common properties and purposes, such as key, code, date, indicator, amount, name, or description.
3. In an ontology, a constraint limiting the classes that can use a property.

domain chaos

A characteristic of multiple attributes using a domain where the domain of valid values used are not internally consistent from attribute to attribute, or are not applied consistently. Example: a unit of measure code domain where one attribute uses the code to show quantity on hand as “doz”, and another shows reorder point quantity in numerals.

domain constraint

SEE constraint, domain.

domain key

SEE key, business.

Domain Name System (DNS)

A hierarchical naming system, built on a distributed database, to associate various information with domain names assigned to each of the participating entities. The DNS serves as the phone book for the Internet by translating human-friendly computer hostnames into IP addresses. This system is managed by Internet Corporation for Assigned Names and Numbers (ICANN).

Domain Name System server

Alternate form: DNS server

The Domain Name System uses a distributed database system architecture based on the client/server model. The nodes are the name servers. Each top-level domain has at least one authoritative DNS server that publishes information about that domain and the name servers of any domains subordinate to it.

domain study

The study of a domain of values for a data item, to determine if that item is similar to another item and a candidate for integration or merging.

Domain/Key Normal Form (DKNF)

SEE Normal Form, Domain/Key.

dot.com

Internet-based companies that rely on digital technology and the use of the Web as the primary communication and interaction media.

downtime

Alternate form: down-time

A general condition wherein users cannot use or access computing systems, applications, data, or information for a broad variety of reasons.

drill across

Data analysis performed across multiple dimensions.

drill anywhere

The ability to “drill down” to any dimension without having to follow predefined drill paths.

drill down

A method of exploring detailed data that was used in creating a summary level of data. Drill down levels depend on the granularity of data within a dimension.

drill through

An OLAP function often used to imply the ability to navigate from dimensionally aggregated data to relational transaction source data. Typically, the transaction set returned is constrained by multiple filters in accordance with the starting dimensional aggregate.

drill up

Data analysis performed on a data set with applied mathematical functions, associated with fewer dimensions, higher levels of hierarchy in one or more dimensions, or both.

Dublin Core

A standard core ontology for meta-data about documents, originating in Dublin Ohio and managed by the Dublin Core Metadata Initiative.

Dublin Core Metadata Initiative (DCMI)

The Dublin Core Metadata Initiative is an open forum engaged in the development of interoperable online meta-data standards that support a broad range of purposes and business models.

dummy key

SEE key, surrogate.

duplex

Adjective. Describes a system that has communication paths in both directions between two parties.

duplicate identification match rule

SEE rule, duplicate identification match.

DW 2.0

DW 2.0 - Advanced Data Warehouse architecture that includes the life cycle of data in the Data Warehouse, the integration of unstructured data, and enterprise metadata.

dynamic data dictionary

A data dictionary that an application program accesses at run time.

Dynamic Data Exchange (DDE)

An industry standard widely accepted by application software for exchanging data among different software programs.

dynamic SQL

Dynamically constructed SQL queries that are not pre-processed, and whose access paths are determined at run time prior to execution.