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Business intelligence (BI) tools do a great job accessing relational databases. In the old days, much of a corporation's data was locked in proprietary or homegrown applications that BI tools could not access directly, which required you to extract the data into a relational database that was often a data warehouse. Currently, much -- if not most -- of a company's operational systems use relational databases, enabling BI to access that data directly. There is a lot of talk about operational BI today, which is when people directly access those operational systems with their BI tools. In those cases a data warehouse is not needed.
But that assumes the ONLY reason people built data warehouses was because their operational data needed to be in a relational format. That simply is not the case.
Data warehousing is not a disease to avoid. It often enables business analysis (performance management and reporting) for business people. This is accomplished by performing the data integration and data cleansing necessary to provide business data that is consistent, correct, current and comprehensive.
Why is this data integration necessary? Too often, data is spread across many applications with different definitions and reference data. This reference data, often referred to as master data management (MDM) or dimensional data (in data warehouse-speak), includes product, customer, employee and other organizational structure data that is not readily available for real-time queries without a data warehouse. In addition, being able to have historical data available for trending and year-over-year analysis is generally best supported by a data warehouse.
It is more than likely that you need a data warehouse and it is best if you plan for one right away. If you fail to plan and build one then you will probably build a series of data silos to support each new set of reporting requirements that you have. This accidental architecture will hurt your business by limiting its visibility into data it needs to operate and grow. It will hurt your IT group, too, because it will be far more costly to create and maintain this haphazard array of data silos than if you were to build the data warehouse from the beginning.
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