When you plan to build a house, you start with what you want and can afford. You decide on architectural style, size and number of rooms. Then you hire an architect to design the house and create a detailed blueprint. The architect gives you feedback on how the various rooms can fit together, what the building codes are and how to fit in the infrastructure such as wiring and plumbing. Most importantly, the architect advises you on what is really possible or practical given your location, house size, wishes, budget and timetable. And she gives you ideas for things you hadnt thought of. Had you skipped this step and gone straight to a builder with your wish list, you would likely go over budget and get a house not well sited on your lot, with poor aesthetics and limited usefulness.
Like the unfortunate house, many data warehouses are built without an architectural blueprint. Companies focus on individual data warehousing (DW)/business intelligence (BI) projects without seeing how they fit as part of an overall architecture. As a result, many DW/BI environments have become a collection of technology, product and data silos that are loosely connected and require an intensive commitment of resources to operate, upgrade, maintain and enhance. Many businesspeople are frustrated with the state of their DW/BI environments, which take forever to enhance and are always a release away from becoming pervasive throughout the enterprise. They remember the investments of time, resources and budget, and they ask why they still have to use spreadsheets (i.e., data shadow systems or spreadmarts) as the superglue for reporting and analysis.
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