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Generic Data Warehouses

Cover for Generic Data Warehouses

Classification: Research Report

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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.

A generic data warehouse is one that tries to be all things to all men. That is to say, it aims to provide a rapid response to all sorts of queries, whether these are simple or complex analytic queries (against transaction level data), aggregated queries running against some sort of OLAP (on-line analytic processing) implementation or simple look-ups that might be required in an active data warehouse. This is a tall order, especially given the fact that many complex analytic queries are unpredictable and cannot be tuned for in advance. For that reason, we have published a sub-domain report on analytic data warehousing as a companion to this report, which discusses the requirements of analytic queries in detail. If you have a significant requirement to support these sorts of queries then that may influence your choice of vendor or you may choose to implement one of the products discussed in this report in conjunction with one of those included in that report.

So, not only does generic mean all things to all men it also means that there is not a particular emphasis on complex and unpredictable analytic queries.

Products evaluated in this report include those from: IBM, Oracle, Microsoft, SAS, Sybase and Teradata.

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