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Enterprise Data Management Terms Paper. Enterprise Data Management Terms
Paper DBM405 University of Phoenix Sean Kern, Facilitator ...
Enterprise Data Management. I am writing a paper about 5 terms that relate to
the enterprise data management. These terms are UML, OLAP vs. ...
... Cash flow forecasts provide important data for estimating ... employ a variety of cash
management techniques to ... the credit profile of an enterprise before entering ...
... hardware could be decommissioned and enterprise licenses returned ... or common schema
for the data records ... would also improve the maintenance and management of the ...
... infrastructure can help alleviate the enterprise problems listed ... Patterns of relations
of data and information and ... of ICT to knowledge management is coping ...
Submitted by patriot338 on June 10, 2006
Category: Technology
Words: 1169 | Pages: 5
Views: 195
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Enterprise Data Management Terms Paper
DBM405
University of Phoenix
Sean Kern, Facilitator
There are various terms that are associated with Enterprise Data Management. Some of these terms are UML, OLAP, OLTP, Data Warehouse, Data Mart and Multi-Tier Architecture. Subsequently, these terms were covered during the five week course of DMB405 and will be explained in further detail throughout the course of the paper. Although the paper will not be all inclusive to the detail of each term, it will touch upon the definition, their use and their place in Enterprise Data Management. The first term that will be discussed is UML and how it relates to the subject at hand.
UML is the industry acronym for the Universal Modeling Language. The Universal Modeling Language is used for software, business, hardware and organizational object structuring. In 1997, with the help of three men and their teams, UML was created and adopted as an industry standard by the Object Management Group (OMG). The Universal Modeling Language is a collaboration of many different people and numerous modeling approaches put together as one unified standard for the purpose of enterprise data management. Not only is it now an industry standard in the United States, but also internationally. UML was created so there were not so many different modeling approaches to arrive at similar conclusions and solutions. Too many approaches can be confusing because things are not uniform. With the creation of a universal standard for modeling, diagramming and conceptual illustration, all stakeholders can in effect, be part of the process and understand the project more thoroughly. The standard creates a common theme amongst the vast array of data that makes up a complicated project and brings it to a level that all can partake in during the analysis and developmental stages.
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