Similarities And Differences Of The Data Warehouse And Data Management Strategy

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A Data Warehouse is a centrally placed storage for data collected from within and outside the organisation. The collected information is organised around key business objectives, and it is utilised during analysis and reporting. It is simply a central database with the sole purpose of analysis and reporting. On the other hand, a Data Mart is much smaller than a Data Warehouse and is applied in a functional area like say finance, where the enterprise adjudges that it would profit from business intelligence. Simply put, a Data Mart can be a single piece or a subset of a Data Warehouse that focuses on a particular enterprise segment. Many Data Marts put together, create a Data Warehouse.
The similarity and differences of the Data Warehouse and
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It emphasises on the kind of data and software combined to deliver information necessary for the implementation of the business strategy. Rouse (2010) identified various data management policies like Data life cycle Management, Master Data Management policy and Big Data Management policy. The Data Life Cycle Management policy focuses on managing how information flows throughout the data’s life cycle. The policy controls data movement from the creation stage until the time the data is deemed obsolete. The other that is Master Data Management strategy enables an enterprise to link all its crucial data together through a master file. The master file would act as the common point of …show more content…
This type of management approach organises the various assets that are data warehousing, business intelligence and database management systems to its corresponding disciplines. Such coordination of the information assets and the data management disciplines ensures that information strategy is appropriately and efficiently aligned to the enterprise’s goals. Such an approach provides strategic business intelligence, business transformation and integration, which enables organisations develop best practices. It brings together previously siloed information technology teams into one coherent camp that can reuse and share information technology systems and in the long-run improve operational excellence. Therefore, the Unified Data Management Strategy brings together segmented divisional use of data into one pool that utilizes similar data analysis tools and

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