Cognos Transformer for Online Analytical Processing
OLAP is a loom to promptly retort the multi-dimensional analytical queries.
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Types of OLAP system
Multidimensional
MOLAP is the standard structure of OLAP and is occasionally referred to as just OLAP. MOLAP stores the data in optimized multi-dimensional array storage, somewhat than in a relational database. So it requires the pre-computation and storage of information in the cube as this operation is called as processing.
Relational
ROLAP works in a straight line with relational databases. Base data and the dimension tables are stored as relational tables and new tables are created to hold the aggregated information that depends on a specialized schema design.
Hybrid
There is no clear agreement across the industry as to what constitutes Hybrid OLAP, except that a database will divide data between relational and specialized storage. For example, for some vendors, a HOLAP database will use relational tables to hold the larger quantities of detailed data, and use specialized storage for at least some aspects of the smaller quantities of more-aggregate or less-detailed data.
Each type has certain benefits, although there is disagreement about the specifics of the benefits between providers.
Some MOLAP implementations are prone to database explosion. Database explosion is a trend causing huge amounts of storage space to be used by MOLAP databases when certain common conditions are met: high number of dimensions, pre-calculated results and sparse multidimensional data. The typical mitigation technique for database explosion is not to materialize all the probable aggregation, but only the finest division of aggregations based on the desired performance or storage trade off.
MOLAP usually delivers superior performance due to dedicated indexing and storage optimizations. MOLAP also needs less storage space compared to ROLAP because the dedicated storage normally includes compression techniques.
ROLAP is generally more scalable. However, large volume pre-processing is difficult to execute resourcefully so it is often skipped. Since ROLAP relies more on the database to perform calculations, it has more limitations in the specialized functions it can use.
HOLAP include a range of solutions that attempt to mix the best of ROLAP and MOLAP. It can generally pre-process quickly, scale well and offer good function support.
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