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Concept
Data management
Summary
Data management comprises all disciplines related to handling data as a valuable resource.
The concept of data management arose in the 1980s as technology moved from sequential processing (first punched cards, then magnetic tape) to random access storage. Since it was now possible to store a discrete fact and quickly access it using random access disk technology, those suggesting that data management was more important than business process management used arguments such as "a customer's home address is stored in 75 (or some other large number) places in our computer systems." However, during this period, random access processing was not competitively fast, so those suggesting "process management" was more important than "data management" used batch processing time as their primary argument. As application software evolved into real-time, interactive usage, it became obvious that both management processes were important. If the data was not well defined, the data would be mis-used in applications. If the process wasn't well defined, it was impossible to meet user needs.
Topics in data management include:
Data governance
Data asset
Data governance
Data trustee
Data custodian or guardian
Data steward
Data subject
Data ethics
Data architecture
Data architecture
Dataflows
Data modeling and design
Database and storage management
Data maintenance
Database administration
Database management system
Business continuity planning
Hierarchical storage management
Data subsetting
Data security
Data access
Data erasure
Data privacy
Data security
Reference and master data
Data integration
Master data management
Reference data
Data Integration and inter-operability
Data movement (ETL, ELT)
Data interoperability
Documents and content
Document management system
Records management
Data warehousing and business intelligence and Analytics
Business intelligence
Data analysis and data mining
Data warehouse and data mart
Data analytics
Metadata
Metadata management
Metadata
Metadata discovery
Metadata publishing
Metadata registry
Data quality
Data discovery
Data cleansing
Data integrity
Data enrichment
Data quality assurance
Secondary data
In modern management usage, the term data is increasingly replaced by information or even knowledge in a non-technical context.
Official source
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