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    <p>I agree with NXC's data warehouse suggestion: </p> <ul> <li>If it was a one-off job, no, but since it is a "reporting application", it is highly likely that many of your reports will fit into the OLAP paradigm.</li> <li>It is obviously a do-able task, as there are many successful OLAP query tools available on the market, with varying degress of complexity</li> <li>OLAP schemas, e.g., the standard <a href="http://en.wikipedia.org/wiki/Star_schema" rel="nofollow noreferrer">star schema</a>, are <strong>designed</strong> to be easy to query. They are flat in nature, with the fact table joining to one or more dimension tables using simple keys in a very straightforward way.</li> <li>the types of operations people will want to do with the reports are predictable: filter, sort, group by, add or remove columns, export to CSV, etc.</li> <li>you will get a good level of flexibility with the reports that get generated - the ability to explore data for various relationships is very addictive</li> <li>once you write the query tool, it is portable for reuse with any other star schema - not bad!</li> <li>"Is it possible to abstract reporting logic and the database schema details?" - yes, OLAP schemas are for exactly this - they make all data conform to a standardized schema. Of course this moves business logic into the ETL layer, but I would argue that is where it belongs.</li> </ul> <p>So, you are required to do ETL with this approach - one option is to do some form of <a href="http://en.wikipedia.org/wiki/ROLAP" rel="nofollow noreferrer">ROLAP</a>, but in practice I have found it to be as easy to write ETL scripts as it is to cajole good performance out of a ROLAP setup.</p>
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    1. COPlus, star schemas are pretty forgiving of exact cardinality of the source data. They are pretty flat, so it's easy to map arbitrary relationships and hierarchies to a set of sensibly chosen dimensions.
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