Data management

Data Management comprises all disciplines related to managing data as a valuable resource.

The data lifecycle

Concept

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

Topics in data management include:

  1. Data Governance
  2. Data Architecture
  3. Data modeling and Design
  4. Database & Storage Management
  5. Data Security
  6. Reference and Master Data
  7. Data Integration and Inter-operability
  8. Documents and Content
  9. Data Warehousing and Business Intelligence
  10. Metadata
  11. Data Quality

Usage

In modern management usage, the term data is increasingly replaced by [

Several organisations have established data management centers (DMC) for their operations.[1]

Integrated data management

Integrated data management (IDM) is a tools approach to facilitate data management and improve performance. IDM consists of an integrated, modular environment to manage enterprise application data, and optimize data-d

  • Automate and simplify operations
  • Provide contextual intelligence across the solution stack
  • Support business growth
  • Accommodate new initiatives without expanding infrastructure
  • Simplify application upgrades, consolidation and retirement
  • Facilitate alignment, consistency and governance
  • Define business policies and standards up front; share, extend, and apply throughout the lifecycle
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See also

References
  1. For example: Kumar, Sangeeth; Ramesh, Maneesha Vinodini (2010). "Lightweight Management framework (LMF) for a Heterogeneous Wireless Network for Landslide Detection". In Meghanathan, Natarajan; Boumerdassi, Selma; Chaki, Nabendu; Nagamalai, Dhinaharan (eds.). Recent Trends in Networks and Communications: International Conferences, NeCoM 2010, WiMoN 2010, WeST 2010,Chennai, India, July 23-25, 2010. Proceedings. Communications in Computer and Information Science. 90. Springer. p. 466. ISBN 9783642144936. Retrieved 2016-06-16. 4.4 Data Management Center (DMC)[:] The Data Management Center is the data center for all of the deployed cluster networks. Through the DMC, the LMF allows the user to list the services in any cluster member belonging to any cluster [...].
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