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I am currently doing reports/datawarehouses/dashboards. When something more complicated that simple questions is needed (see Data Warehousing for Cavemen), ad-hoc queries are quite often not the answer anymore, either with NoSQL or with SQL.

I don't want my clients to be dependent on me (or someone else) to build complicated SQL queries when they have questions, so I focus on getting an easy to maintain facts/dimensions model (as advocated by Ralph Kimball http://www.amazon.com/Data-Warehouse-Toolkit-Complete-Dimens...) which can evolve if needed.

The nice point about MongoDB when doing this is that it makes it a lot easier to add attributes to dimensions, or load the data, or evolve the reporting system in general (and I like that).

You can apply the same principles to build dimensions/facts based data structure and answer questions that SQL alone wouldn't be able to answer easily.

Example of such question: how many calls did we receive during french legal week #9 that were handled by team X outside the normal working hours or while we were in vacations ? In those calls, how many were issued by a woman (as it has a financial impact in this case) ?




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