Enterprise Data Management

1169 Words3 Pages

Enterprise Data Management

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...

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... livelihood of the organization and understanding the role and place of each aspect is crucial. Realizing there are industry standards for modeling and diagramming help keep all stakeholders on the same project page. Proper use and approach of OLAP is key along with the setup and utilization of data warehouses and marts. Finally there is the architecture you use to tie it all together. Each area builds upon the other and is successive steps in the stages of the Systems Development Life Cycle. Although each is different, they all share a common interest. This interest is to work together to complete a whole data system that the entire corporation can use effectively and enjoy.

References

Retrieved from the World Wide Web on February 19, 2006

http://en.wikipedia.org/wiki/UML

Retrieved from the World Wide Web on February 19, 2006

http://en.wikipedia.org/wiki/Olap

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