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I would suggest reading some books on the topic of Dimensional Modeling [1] such as "The Data Warehouse Toolkit" [2]. The critical thing you need to expose to your users is the ability to ask for things which make sense in their world that are actually really difficult for even an engineer to code. Things like: "Show me average 9am-12pm sales on Mondays, Wednesday and Fridays for 1st quarter, 2012"

  [1] http://en.wikipedia.org/wiki/Dimensional_modeling
  [2] http://www.amazon.com/Data-Warehouse-Toolkit-Complete-Dimensional/dp/0471200247



Speaking as someone who does his fair share of dimensional modeling, I would just point out that the example you cite could only involve two tables in a well designed dimensional model (sales fact and time/date dimension, I reckon). The challenge is in getting to that point.

To speak to OPs point about difficulty in querying data warehouses, most business intelligence tools that I'm aware of provide semantic layer[1]-type capabilities, whereby the user interface of the tool is presented in the language of the business domain. Nevertheless, I still agree that this is still difficult work, unfortunately. That it is getting more complicated in some respects, such as through unstructured data, doesn't help either.

[1] http://en.wikipedia.org/wiki/Semantic_layer


I guess I wasn't clear enough if I came across like my example was complex. It's one easily solved via DM and one that's extremely hard to execute in most non-dimensionally-modeled setups. That's exactly why I'm a huge advocate of DM instead of just throwing a ton of servers, hadoop & MR at everything.




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