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Data management

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

The data lifecycle

Concept Edit

The concept of data management arose in the 1980s as technology moved from sequential processing [1] (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 Edit

Topics in data management include:

Usage Edit

In modern management usage, the term data is increasingly replaced by information or even knowledge in a non-technical context. Thus data management has become information management or knowledge management. This trend obscures the raw data processing and renders interpretation implicit. The distinction between data and derived value is illustrated by the information ladder. However, data has staged a comeback with the popularisation of the term big data, which refers to the collection and analyses of massive sets of data.

Several organisations have established data management centers (DMC) for their operations.[2]

See also Edit

References Edit

  1. ^ Hoare, C. A. R. (2004) [1985]. Communicating Sequential Processes. Prentice Hall International. ISBN 978-0-13-153271-7.
  2. ^ 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. Vol. 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 [...].
  3. ^ "Data Mesh: Delivering data-driven value at scale".

External links Edit

  •   Media related to Data management at Wikimedia Commons
  • Data management at Curlie

data, management, comprises, disciplines, related, handling, data, valuable, resource, data, lifecycle, contents, concept, topics, usage, also, references, external, linksconcept, editthis, section, does, cite, sources, please, help, improve, this, section, ad. Data management comprises all disciplines related to handling data as a valuable resource The data lifecycle Contents 1 Concept 2 Topics 3 Usage 4 See also 5 References 6 External linksConcept EditThis section does not cite any sources Please help improve this section by adding citations to reliable sources Unsourced material may be challenged and removed Find sources Data management news newspapers books scholar JSTOR April 2020 Learn how and when to remove this template message The concept of data management arose in the 1980s as technology moved from sequential processing 1 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 EditTopics 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 dataUsage EditIn modern management usage the term data is increasingly replaced by information or even knowledge in a non technical context Thus data management has become information management or knowledge management This trend obscures the raw data processing and renders interpretation implicit The distinction between data and derived value is illustrated by the information ladder However data has staged a comeback with the popularisation of the term big data which refers to the collection and analyses of massive sets of data Several organisations have established data management centers DMC for their operations 2 See also EditOpen data FAIR data Pseudonymization Information architecture Enterprise architecture Information design Information system Controlled vocabulary Data curation Data retention Data Management Association Data management plan Data mesh a domain oriented data architecture 3 Computer data storage Data proliferation Digital preservation Document management Enterprise content management Hierarchical storage management Information repository Machine readable document Performance report System integration Customer data integration Identity management Identity theft Data theft ERP software CRM softwareReferences Edit Hoare C A R 2004 1985 Communicating Sequential Processes Prentice Hall International ISBN 978 0 13 153271 7 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 Vol 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 Data Mesh Delivering data driven value at scale External links Edit nbsp Media related to Data management at Wikimedia Commons Data management at Curlie Retrieved from https en wikipedia org w index php title Data management amp oldid 1167055176, wikipedia, wiki, book, books, library,

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