D - Definitions

  • D

    dark data

    Dark data is digital information that is not being used. Consulting and market research company Gartner Inc. describes dark data as "information assets that an organization collects, processes and stores in the course of its regular business activity, but generally fails to use for other purposes."

  • data

    In computing, data is information that has been translated into a form that is efficient for movement or processing.

  • data access rights

    A data access right (DAR) is a permission that has been granted that allows a person or computer program to locate and read digital information at rest. Digital access rights play and important role in information security and compliance.

  • data activation

    Data activation is a marketing approach that uses consumer information and data analytics to help companies gain real-time insight into target audience behavior and plan for future marketing initiatives.

  • data analytics (DA)

    Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information.

  • Data as a Service (DaaS)

    Data as a Service (DaaS) is an information provision and distribution model in which data files (including text, images, sounds, and videos) are made available to customers over a network, typically the Internet.

  • data catalog

    A data catalog is a metadata management tool designed to help organizations find and manage large amounts of data – including tables, files and databases – stored in their ERP, human resources, finance and e-commerce systems as well as other sources like social media feeds.

  • data classification

    Data classification is the process of organizing data into categories that make it is easy to retrieve, sort and store for future use.

  • data dredging (data fishing)

    Data dredging, sometimes referred to as data fishing is a data mining practice in which large volumes of data are searched to find any possible relationships between data...

  • data engineer

    A data engineer is a worker whose primary job responsibilities involve preparing data for analytical or operational uses.

  • data federation software

    Data federation software is programming that provides an organization with the ability to collect data from disparate sources and aggregate it in a virtual database where it can be used for business intelligence (BI) or other analysis.

  • data integration

    Data integration is the process of combining data from multiple source systems to create unified sets of information for both operational and analytical uses.

  • data management-as-a-service (DMaaS)

    Data Management-as-a-Service (DMaaS) is a type of cloud service that provides protection, governance and intelligence across a company’s various data sources.

  • data mart (datamart)

    A data mart is a repository of data that is designed to serve a particular community of knowledge workers.

  • data modeling

    Data modeling is the process of documenting a complex software system design as an easily understood diagram, using text and symbols to represent the way data needs to flow.

  • data profiling

    Data profiling is the process of examining, analyzing and reviewing data to collect statistics surrounding the quality and hygiene of the dataset.

  • data quality

    Data quality is a measure of the condition of data based on factors such as accuracy, completeness, consistency, reliability and whether it's up to date.

  • 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 silo

    A data silo exists when an organization's departments and systems cannot, or do not, communicate freely with one another and encourage the sharing of business-relevant data.

  • data stewardship

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

  • data transformation

    Data transformation is the process of converting data from one format, such as a database file, XML document or Excel spreadsheet, into another.

  • 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

    A data warehouse is a federated repository for all the data collected by an enterprise's various operational systems, be they physical or logical.

  • 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 as a service (DBaaS)

    Database as a service (DBaaS) is a cloud computing managed service offering that provides access to a database without requiring the setup of physical hardware, the installation of software or the need to configure the database.

  • database replication

    Database replication is the frequent electronic copying of data from a database in one computer or server to a database in another -- so that all users share the same level of information.

  • 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 Agile approach to designing, implementing and maintaining a distributed data architecture that will support a wide range of open source tools and frameworks in production. The goal of DataOps is to create business value from big data. 

  • 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.

  • deterministic/probabilistic data

    Deterministic and probabilistic are opposing terms that can be used to describe customer data and how it is collected. Deterministic data is also referred to as first party data. Probabilistic data is information that is based on relational patterns and the likelihood of a certain outcome.

  • 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.

  • dirty data

    In a data warehouse, dirty data is a database record that contains errors.

  • 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.

  • What is data governance and why does it matter?

    Data governance (DG) is the process of managing the availability, usability, integrity and security of the data in enterprise systems, based on internal data standards and policies that also control data usage.

  • What is data management and why is it important?

    Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization, as explained in this in-depth look at the process.

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