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2. Data management - Wikipedia

   en.wikipedia.org/wiki/Data_management

   Data management comprises all disciplines related to handling data as a valuable resource, it is the practice of managing an organization's data so it can be analyzed for decision making. [ 1 ] Concept

3. Enterprise data management - Wikipedia

   en.wikipedia.org/wiki/Enterprise_data_management

   Enterprise data management (EDM) is the ability of an organization to precisely define, easily integrate and effectively retrieve data for both internal applications and external communication. EDM focuses on the creation of accurate, consistent, and transparent content.

4. Data stream management system - Wikipedia

   en.wikipedia.org/wiki/Data_stream_management_system

   A data stream management system (DSMS) is a computer software system to manage continuous data streams. It is similar to a database management system (DBMS), which is, however, designed for static data in conventional databases. A DBMS also offers a flexible query processing so that the information needed can be expressed using queries.

5. Data management platform - Wikipedia

   en.wikipedia.org/wiki/Data_management_platform

   Data management platforms rely heavily on Cookie technology to identify behaviours. Recent moves from Apple and now Google are moving towards blocking third party advertising cookies which places the Data management platform value proposition at risk. Moreover, the adoption of such a platform may be difficult in an organization's current ...

6. Category:Database management systems - Wikipedia

   en.wikipedia.org/wiki/Category:Database...

   A database management system (DBMS) is a computer program (or more typically, a suite of them) designed to manage a database, a large set of structured data, and run operations on the data requested by numerous users. Typical examples of DBMS use include accounting, human resources and customer support systems.

7. Master data management - Wikipedia

   en.wikipedia.org/wiki/Master_data_management

   Challenges in adopting master data management within large organizations often arise when stakeholders disagree on a "single version of the truth" concept is not affirmed by stakeholders, who believe that their local definition of the master data is necessary. For example, the product hierarchy used to manage inventory may be entirely different ...