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2010-01-02T20:38:33.967
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2018-08-23T21:06:38.910
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2018-08-23T21:06:38.910
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<ol> <li>You should consider building a data warehouse, when two of the following criteria match: <ul> <li>Huge amount of data</li> <li>Many big complex selects (possibly compared to few inserts, updates, and deletes) that just take too long to execute (and are complicated to write)</li> <li>Data from different systems needs to get combined</li> </ul></li> <li>It's really the question what you consider a data warehouse. In many cases you can move gradually from OLTPs Systems with some reports to a full blown data warehouse, as long as you can stick to a relational database management system. First could be to build a first fact table, and keep using the normalized tables for dimension. Then adding more facts, more fact tables or dedicated dimension tables to the game. First in the same database (or one of the databases of the involved systems), possibly moving to a separate database later.</li> <li>A full data warehouse (separate database, star schema) offers the best options for tuning select statements, apart from going to a specialized system. It is also cleanly decoupled from the OLTP system(s). Think schema design, but also resources like CPU, I/O and memory and organizational, like scheduling of new releases. Of course it is a lot of work which you possibly don't need.</li> <li>It's in the answers above: just because you have a handfull of complex queries, doesn't mean you should build a DWH, same holds for the other criteria, if they come in isolation.</li> <li>Can't offer much here, but the advice: go agile. The requirements for a DWH depend extremly on the possibilities the users see. There for requirements are likely to change. Automating tests with databases is a pain, but fooling around in a production system with no proper tests is worse.</li> </ol>
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1. POData Warehouse Considerations: When and Why?
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1. USJens Schauder
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