Business intelligencey glossary

Business intelligence and data warehousing technologies are heavy on jargons. There are specific terms to define specific method and processes. For a beginner, it may be confusing to go through a technical paper to grasp clear understanding.

Data mining fundamentals

A grocery chain used the data mining capacity of a software to analyze local buying patterns. They discovered that when men bought diapers on Thursdays and Saturdays, they also tended to buy beer. Further analysis showed that these shoppers typically did their weekly grocery shopping on Saturdays. On Thursdays, however, they only bought a few items. The retailer concluded that they purchased the beer to have it available for the upcoming weekend.

OLAP - Online Analytics Processing Example

OLAP stands for OnLine Analytical Processing and it deals with Historical Data or Archival Data. Historical data are those data that are archived over a long period of time. OLAP helps to answer multi-dimensional analytical (MDA) queries in a fast manner.

Kimball and Inmon Approaches to Data Warehousing

Both Bill Inmon and Ralph Kimball are stalwarts of data warehousing and business intelligence industry, they have contributed immensely to define standards and frameworks. They each have defined methods to design data warehouse for any company. Both philosophies have their own advantages and differentiating factors, and enterprises continue to use either of these.

Benefits of business intelligence

Today it is not just the large organizations, be it a small company or a midsized firm - every moden company needs some kind of business intelligence solution to be competitive in the market.