Data Warehousing - Multidimensional OLAP
Multidimensional OLAP (MOLAP) uses the array-based multidimensional storage engines for multidimensional views of data. With multidimensional data stores, the storage utilization may be low if the data set is sparse. Therefore many MOLAP Server uses the two level of data storage representation to handle dense and sparse data sets.
Points to remember:
MOLAP tools need to process information with consistent response time regardless of level of summarizing or calculations selected.
The MOLAP tools need to avoid many of the complexities of creating a relational database to store data for analysis.
The MOLAP tools need fastest possible performance.
MOLAP Server adopts two level of storage representation to handle dense and sparse data sets.
Denser subcubes are identified and stored as array structure.
Sparse subcubes employs compression technology.
MOLAP includes the following components.
Front end tool
Here is the list of advantages of Multidimensional OLAP
MOLAP allows fastest indexing to the precomputed summarized data.
Helps the user who are connected to a network and need to analyze larger, less defined data.
Easier to use therefore MOLAP is best suitable for inexperienced user.
MOLAP are not capable of containing detailed data.
The storage utilization may be low if the data set is sparse.
MOLAP vs ROLAP
|1||The information retrieval is fast.||Information retrieval is comparatively slow.|
|2||It uses the sparse array to store the data sets.||It uses relational table.|
|3||MOLAP is best suited for inexperienced users since it is very easy to use.||ROLAP is best suited for experienced users.|
|4||The separate database for data cube.||It may not require space other than available in Data warehouse.|
|5||DBMS facility is weak.||DBMS facility is strong.|