BI is the new buzzword in the IT community. It has the promise to fulfill the decision-support needs of a business enterprise.
BI works behind-the-scenes. It sits on top of the enterprise’s relational databases and builds what are called OLAP cubes, which contain the business data that can be seen at once from several perspectives.
While enterprise database software like Oracle and SQL server provide BI tools out-of-the-box, they are highly integrated into their specific databases. They offer no help to those multitudes of enterprises that do not keep their data in these databases.
It becomes imperative, therefore, to build a BI tool that can work with any relational database. Building such a tool is not an easy task. In fact, it will be a very ambitious project, given the myriad database servers that are rampant in the industry today.
The open source community took the initiative in the BI space and has come up with a BI framework. It is called Pentaho and is now making waves in the industry.
Pentaho provides BI tools like analysis and reporting services, among a host of services aimed at the enterprise needs. Pentaho bundles these services in a way that each service is toolable independently of other services. These services may also be used together all in one, or in different combination of pieces thereof.
A business enterprise selling a myriad products in a dozen different geographical regions generating revenues every quarter and annually relies heavily on tools that can provide analysis on sale by type of product, quantity, region and time and generate reports that aid future decision-making.
Such analysis and report generation in a number of ways like pivot tables and charts has been traditionally linked to OLAP, online analytical processing. OLAP builds a multidimensional data grid that is centered on a fact table linked to an array of dimension tables around it in a typical star pattern. OLAP data comes from the traditional relational databases, which is sliced and diced according to the needs of the enterprise and presented in a manner that is most appropriate to decision making.
OLAP data is packed inside what is called a cube. The OLAP cube provides a multi-faceted view of the data, which can then be presented graphically via tools like Pentaho or BIRT. In this sense OLAP presents a Fast Access to Shared Multi-dimensional Information (FASMI), according to a generally agreed definition. Any tool that runs in the BI space must conform to these features.