Data Warehousing and Data Mining

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Data Warehouses and Data Marts: A Dynamic View

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Data Warehouses and Data Marts: A Dynamic View By Joseph M. Firestone, Ph.D. White Paper No. Three March 27, 1997

Patterns of Data Mart Development In the beginning, there were only the islands of information: the operational data stores and legacy systems that needed enterprise-wide integration; and the data warehouse: the solution to the problem of integration of diverse and often redundant corporate information assets. Data marts were not a part of the vision. Soon though, it was clear that the vision was too sweeping. It is too difficult, too costly, too impolitic, and requires too long a development period, for many organizations to directly implement a data warehouse. A data mart, on the other hand, is a decision support system incorporating a subset of the enterprise’s data focused on specific functions or actvities of the enterprise. Data marts have specific business-related purposes such as measuring the impact of marketing promotions, or measuring and forecasting sales performance, or measuring the impact of new product introductions on company profits, or measuring and forecasting the performance of a new company division. Data Marts are specific business-related software applications. Data marts may incorporate substantial data, even hundreds of gigabytes, but they contain much less data than would a data warehouse developed for the same company. Also since data marts are focused on relatively specific business purposes, system planning and requirements analysis are much more manageable processes, and consequently design, implementation, testing and installation are all much less costly than for data warehouses. In brief, data marts can be delivered in a matter of months, and for hundreds of thousands, rather than millions of dollars. That defines them as within the range of divisional or departmental budgets, rather than as projects needing enterprise level funding. And that brings up politics or project justification. Data marts are easier to get through politically for at least three reasons. First, because they cost less, and often don’t require digging into organization-level budgets, they are less likely to lead to interdepartmental conflicts. Second, because they are completed quickly, they can quickly produce models of success and corporate 1 of 14

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Data Warehouses and Data Marts: A Dynamic View

file:///E|/FrontPage Webs/Content/EISWEB/DWDMDV.html

constituencies that will look favorably on data mart applications in general. Third, because they perform specific functions for a division or department that are part of that unit’s generally recognized corporate or organizational responsibility, political justification of a data mart is relatively clean. After all, it is self-evident that managers should have the best decision support they can get provided costs are affordable for their business unit, and the technology appears up to the job. Perhaps for the first time in computing history those conditions may exist for DSS applications. So, data marts have become a popular alternative to data warehouses. As this alternative has gained in popularity, however, at least three different patterns or informal models of data mart development have appeared. The first response to the call for data mart development was the view that data marts are best characterized as subsets (often somewhat or highly aggregated) of the data warehouse, sited on relatively inexpensive computing platforms that are closer to the user, and are periodically updated from the central data warehouse. In this view, the data warehouse is the parent of the data mart. The second pattern of development denies the data warehouse its place of primacy and sees the data mart as independently derived from the islands of information that predate both data warehouses and data marts. The data mart uses data warehousing...
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