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move it into a canned data mart. This canned data mart will have all the common queries your users will want and all the other setup work done. You can have such a data mart up in a matter of a few weeks instead of the months it might take you to implement it yourself.

OLAP Engines

You might run across alternative data warehouse database technologies. Oracle even has one of these databases in its Express product line. These databases store data in an alternative data storage format that looks more like a multidimensional cube instead of a flat table with rows and columns . Although this is a more confusing format that is not well suited to transaction processing, it is very well suited for handling complex what-if queries in which you want to drill down in a number of dimensions or compare two what-if scenarios. If you have needs in these areas, you should investigate the various products that are out there. The OLAP and RDBMS worlds are not incompatible, though. One common scenario is to use an Oracle database to store bulk information and then to load part of this data into the analytical processing database for analysis.

Summary

This chapter covers a lot of ground in a few pages. Again, if you really want to get into more detail on data warehouses and data marts, a number of books can provide you with the details you need. This chapter gives you an overview of the various processes involved in a data warehouse and the forms and formats the data can take on its way from the source systems to the data warehouse. A number of success stories are out there in which data warehouses have been invaluable tools to help businesses make the right decisions and save money. Perhaps your business is one of those that can take advantage of this technology.

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