Data Access

The act of reading the data warehouse by end users via reporting or analytical tools. 

Data Acquisition

The extract, transformation, integration, transport and loading of data from one structure to another. Applies to the population of atomic level and secondary level data structures. See also acquisition architecture.

Data Cleanliness

A quality indicator of a data store related to how much errant data it contains. See also data quality, data completeness, and data correctness.

Data Completeness

A quality indicator of a data store related to how much data it may be missing. See also data quality, data cleanliness, and data correctness. see data quality

Data Conversion

See conversion.

Data Correctness

A quality indicator of a data store related to how accurate the data is. See also data quality, data cleanliness, and data completeness.

Data Extract

See extract.

Data Fusion

see data integration

Data Integration

See integration

Data Load

Populating a database from a load file. This may include use of a batch data load utility. Also refers to the load file itself.

Data Mapping

Matching source and target data elements to specify where data warehouse elements will be sourced from.

Data Mart

A form of simplified DW implementation, or a component of an architected data warehouse, which is based on data collected directly from source systems. This data is used for a specific departmental rather than an enterprise level decision support purpose.

Data Mining

Automated analysis of data to unearth previously undiscovered data correlation.

Data Model

A data representation which illustrates data entities and elements and the relationships among them. See conceptual data model, logical data model, and physical data model.

Data Quality

A term that indicates one or more pertains to issues of: accuracy, integrity, cleanliness, correctness, completeness, and consistency. The quality of data is often evaluated to determine usability and to establish the processes necessary for improving data quality. Data quality may be measured objectively or subjectively.

Data Staging Area

An area set aside in a database or disks for loading and testing data prior to loading into the production environment. The staging area provides the opportunity to process or validate data without affecting the production DW environment.

Data Steward

An individual who is largely responsible for data definitions, data usage, and data quality.

Data Warehouse

An integrated, subject oriented collection of data which captures data at incremental moments of time and retains them for a long period of time. Data warehouses are usually designed to enhance decision support functions. Architected data warehouses contain a single atomic level and multiple secondary levels of data to support particular decision support functions.

Data Warehouse  Architecture

See acquisition architecture, information architecture.

Data Warehouse Characteristics

Those parameters of the processes that typify the nature of an iteration (e.g. focus, activities to be performed, etc.).

Data Warehouse Data

See data warehouse

Data Warehouse Model

A data model that supports informational or analytical processing rather than operational processing. Data warehouse models introduce controlled redundancy, subject orientation, and summary tables among other non-conventional modeling techniques. See also data warehouse, information architecture.

Decision Support System (DSS)

An information system used to assist in tactical or strategic business decision-making activities. Usually DSS involves the analysis of integrated, subject oriented, historical data.

Default Values

The content that a data element is assigned if not assigned by any other business rule or process.

Departmental Data Warehouse

A limited data warehouse used expressly to solve a particular business problem for a single business unit. It may include aggregated or sub-selected data acquired directly from source systems. See also data mart.

Departmental Level

The tables in a data warehouse used for a specific departmental purpose or to solve a particular business problem. This may include aggregated or sub-selected data from the atomic layer. See also atomic level, data mart, and secondary level.

Departmentally Structured

See departmental level.

Derived Data

Data that is fabricated or calculated based on some business rule from other data

Drill Down

The activity of navigating from high level data to detailed data (e.g. summary level to atomic level) using a data query/analysis tool.