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Data Management
The second edition of the DAMA Data Management Body of Knowledge (DMBOK2) refers to data management as: "The development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycles."[1]
The DAMA-DMBOK2 lists 11 knowledge areas for data management: data architecture, data modeling, data storage and operations, data security, data integration and interoperability, document and content management, reference and master data management, data warehousing and business intelligence, metadata management, data quality, and data governance.
According to Gartner, "Data management (DM) consists of the practices, architectural techniques, and tools for achieving consistent access to and delivery of data across the spectrum of data subject areas and data structure types in the enterprise, to meet the data consumption requirements of all applications and business processes."
[2]
SAS defines data management as: "The practice of managing data as a valuable resource to unlock its potential for an organization."[3]
Informatica refers to data management as: "The implementation of policies and procedures that put organizations in control of their business data regardless of where it resides."[4]
// Proper data management can greatly improve the efficacy of an enterprise's data.
See also:
- ↑ https://dama.org/content/what-data-management
- ↑ https://www.gartner.com/en/information-technology/glossary/dmi-data-management-and-integration
- ↑ https://www.sas.com/en_ca/insights/data-management/data-management.html
- ↑ https://www.informatica.com/ca/services-and-training/glossary-of-terms/data-management-definition.html
