Data architecture: Difference between revisions

Revision as of 06:08, 27 July 2016

Revision as of 10:17, 14 October 2016

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Without the guidance of a properly implemented data architecture design, common data operations might be implemented in different ways, rendering it difficult to understand and control the flow of data within such systems. This sort of fragmentation is highly undesirable due to the potential increased cost, and the data disconnects involved. These sorts of difficulties may be encountered with rapidly growing enterprises and also enterprises that service different lines of [[business]] (e.g. [[insurance]] [[Product (business)|products]]).

Properly executed, the data architecture phase of information system planning forces an organization to precisely specify and describe both internal and external information flows. These are patterns that the organization may not have previously taken the time to conceptualize. It is therefore possible at this stage to identify costly information shortfalls, disconnects between departments, and disconnects between organizational systems that may not have been evident before the data architecture analysis.<ref>{{cite book|last=Mittal|first=Prashant|title=Author|year=2009|publisher=Global India Publications|___location=pg 256|isbn=978-93-8022-820-4|pages=314|url=httphttps://books.google.com/books?id=BpkhYDj4tm0C&dq=inauthor:%22PRASHANT+MITTAL%22&source=gbs_navlinks_s}}</ref>

== Constraints and influences ==