Data Management/Data Warehousing Definitions

This glossary explains the meaning of key words and phrases that information technology (IT) and business professionals use when discussing data management and related software products. You can find additional definitions by visiting WhatIs.com or using the search box below.

  • D

    data profiling

    Data profiling, also called data archeology, is the statistical analysis and assessment of the quality of data values within a data set for consistency, uniqueness and logic.  

  • data quality

    In computing, data quality is the reliability and application efficiency of data, particularly when kept in a data warehouse. Data quality assurance (DQA) is the process of verifying the reliability and efficiency of data.

  • data scrubbing (data cleansing)

    Data scrubbing, also called data cleansing, is the process of cleaning up data in a database that is incorrect, incomplete, or duplicated.

  • data stewardship

    Data stewardship is the management and oversight of an organization's data assets to provide business users with high quality data that is easily accessible in a consistent manner.

  • data virtualization

    Data virtualization is an umbrella term used to describe any approach to data management that allows an application to retrieve and manipulate data without needing to know any technical details about the data such as how it is formatted or where it is physically located. 

  • data warehouse as a service (DWaaS)

    Data warehousing as a service (DWaaS) is an outsourcing model in which a service provider configures and manages the hardware and software resources a data warehouse requires, and the customer provides the data and pays for the managed service.

  • database-agnostic

    Database-agnostic is a term describing the capacity of software to function with any vendor’s database management system (DBMS). In information technology (IT), agnostic refers to the ability of something – such as software or hardware – to work with various systems, rather than being customized for a single system.

  • DataOps (data operations)

    DataOps (data operations) is an approach to designing, implementing and maintaining a distributed data architecture that will support a wide range of open source tools and frameworks in production.

  • denormalization

    In a relational database, denormalization is an approach to optimizing performance in which the administrator selectively adds back specific instances of duplicate data after the data structure has been normalized.

  • dimension

    In data warehousing, a dimension is a collection of reference information about a measurable event (fact).

  • dimension table

    A dimension table is a table in a star schema of a data warehouse. A dimension table stores attributes, or dimensions, that describe the objects in a fact table.

  • disambiguation

    Disambiguation (also called word sense disambiguation) is the act of interpreting the intended sense or meaning of a word. Disambiguation is a common problem in computer language processing, since it is often difficult for a computer to distinguish a word’s sense when the word has multiple meanings or spellings.

  • E

    entity relationship diagram (ERD)

    An entity relationship diagram (ERD), also known as an entity relationship model, is a graphical representation of an information system that depicts the relationships among people, objects, places, concepts or events within that system.

  • Extract, Load, Transform (ELT)

    Extract, Load, Transform (ELT) is a data integration process for transferring raw data from a source system to a target database and then preparing the information for downstream uses.

  • extract, transform, load (ETL)

    In managing databases, extract, transform, load (ETL) refers to three separate functions combined into a single programming tool.

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