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DATA WAREHOUSING FUNDAMENTALS: A Comprehensive Guide for IT Professionals by Paulraj Ponniah

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3.4. EMERGENCE OF STANDARDS

Think back to our discussion in Chapter 1 of the data warehousing environment as blend of many technologies. A combination of multiple types of technologies is needed for building a data warehouse. The range is wide: data modeling, data extraction, data transformation, database management systems, control modules, alert system agents, query tools, analysis tools, report writers, and so on.

Now in a hot industry such as data warehousing, there is no scarcity of vendors and products. In each of the multitude of technologies supporting the data warehouse, numerous vendors and products exist. The implication is that when you build your data warehouse, many choices are available to you to create an effective solution with the best-of-breed products. That is the good news. However, the bad news is that when you try to use multivendor products, the result could also be total confusion and chaos. These multivendor products have to cooperate and work together in your data warehouse.

Unfortunately, there are no established standards for the various products to exchange information and function together. When you use the database product from one vendor, the query and reporter tool from another vendor, and the OLAF (online analytical processing) product from yet another vendor, these three products have no standard method for exchanging data. Standards are especially critical in two areas: metadata interchange and OLAP functions.

Metadata is like the total roadmap ...

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