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This report is one of four that Bloor Research has published on data warehousing, which consist of a domain report and three sub-domain reports as follows:

• Generic data warehouses - for environments where a single database is supposed to do everything.
• Analytic data warehouses - for environments (complex and unpredictable analytic queries) where a generic approach may not be suitable and it may be appropriate to employ two separate databases or, at least, a different generic database.
• Packaged data warehouses - packages for automating the creation of your data warehouse and data marts.

In our view, conventional approaches to data warehousing do not handle analytic queries, and especially complex questions of this type, very well. In this report we need to consider why that is the case so that we can understand the sorts of solutions that are available to resolve this problem. Before we begin let us briefly re-iterate out definition of an analytic query, which we take to be any query that starts with the premise that it needs access to transaction-level (as opposed to aggregated) data.

This report focuses particularly, though not exclusively, on data warehouse appliances including: Netezza, DATAllegro, GreenPlum, Kognitio (WhiteCross), Calpont and Teradata plus SAND Analytic Server and Sybase IQ.

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