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

Contents

Overview

The official definition provided by DAMA or Boucher: "Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise."[citation needed] This definition is fairly broad and encompasses a number of professions which may not have direct technical contact with lower-level aspects of data management, such as relational database management.

Alternatively, the definition provided in the DAMA Data Management Body of Knowledge (DAMA-DMBOK) is: "Data management is the development, execution and supervision of plans, policies, programs and practices that control, protect, deliver and enhance the value of data and information assets."[1]

Topics in Data Management

Topics in Data Management, grouped by the DAMA DMBOK Framework[2], include:

  1. Data Governance
  2. Data Architecture, Analysis and Design
  3. Database Management
  4. Data Security Management
  5. Data Quality Management
  1. Reference and Master Data Management
  2. Data Warehousing and Business Intelligence Management
  3. Document, Record and Content Management
  4. Meta Data Management

Body Of Knowledge

The DAMA Guide to the Data Management Body of Knowledge" (DAMA-DMBOK Guide), under the guidance of a new DAMA-DMBOK Editorial Board. This publication is available from April 5, 2009.

Usage

The neutrality of this section is disputed. Please see the discussion on the talk page. Please do not remove this message until the dispute is resolved. (December 2007)

In modern management usage, one can easily discern a trend away from the term 'data' in composite expressions to the term information or even knowledge when talking in non-technical context. Thus there exists not only data management, but also information management and knowledge management. This is a fairly detrimental tendency in that it obscures the fact that is usually always plain, traditional data that is managed or somehow processed on second looks. The extremely relevant distinction between data and derived values can be seen in the information ladder. While data can exist as such, 'information' and 'knowledge' are always in the "eye" (or rather the brain) of the beholder and can only be measured in relative units.

See also

External links

Notes

  1. ^ http://www.dama.org/files/public/DI_DAMA_DMBOK_Guide_Presentation_2007.pdf "DAMA-DMBOK Guide (Data Management Body of Knowledge) Introduction & Project Status"
  2. ^ http://www.dama.org/i4a/pages/index.cfm?pageid=3364 "DAMA-DMBOK Functional Framework"

Categories: Data management

 

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