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Olap Servers For Your Business

Olap Servers For Your Business

Online Analytical Processing gives access to tremendous amounts of data to end users

in a fast and simple manner to play a vital role in investigative reasoning. In principle, multidimensional data representations, also known as cubes, are used by OLAP Servers to facilitate this access. Talking purely in terms of business online analytical processing is a vital aspect that needs to be addressed with utmost care and consideration, since it plays an important role in the decision-making of an organization.

Generally, OLAP servers are used for the following reasons:

Support complex analysis for large input data sets (atomic-level)

Data analysis from among numerous business dimensions

Deliver simplified analysis to decision makers

There are basically two architectures for OLAP systems MOLAP (multidimensional OLAP) and ROLAP (relational OLAP). The former (MOLAP) uses a multidimensional database for providing the analysis, and the ROLAP architecture directly accesses data from the warehouses. There is also a difference of view in the architects of both these platforms. MOLAP architects believe that OLAP's perfect utilization is in multidimensional storage of data, while proponents of ROLAP state that OLAP is best used with a relational database. Let's take a look at some points of difference.

OLAP Servers based on the ROLAP platform are neutral to the aggregation on the database, and hence give the option of deciding the preference between query response time and batch processing requirements to the system designer. On the other hand, MOLAP calls for the pre-compilation of the database to deliver reasonable query performance.

ROLAP is meant for dynamic data consolidation for the purpose of decision-support analysis, and MOLAP is intended for batch consolidation.

ROLAP can work effectively on as many dimensions as the organization or business process requires it to. MOLAP usually performs optimally on less than ten dimensions.

OLAP analysis for large amounts of data input is supported by ROLAP, but MOLAP works best only in case the input data set is less than 5 GB in size.

by: Carlos Quijada
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