On-Line Analytic Processing (OLAP)

The term On-Line Analytic Processing (OLAP) [or Fast Analysis of Shared Multidimensional Information (FASMI)] refers to technology that allows users of multidimensional databases to generate on-line descriptive or comparative summaries (views) of data and other analytic queries. Note that despite its name, analyses referred to as OLAP do not need to be performed truly on-line (or in real-time); the term applies to analyses of multidimensional databases (that can, obviously, contain dynamically updated information) through efficient multidimensional queries that reference various types of data.

OLAP facilities can be integrated into corporate (enterprise-wide) database systems, and they allow analysts and managers to monitor the performance of the business ( such as various aspects of the manufacturing process or numbers and types of completed transactions at different locations) or the market. The final result of OLAP techniques can be very simple ( frequency tables, descriptive statistics, simple cross-tabulations) or more complex ( they can involve seasonal adjustments, removal of outliers, and other forms of cleaning the data).

Although Data Mining techniques can operate on any kind of unprocessed or even unstructured information, they can also be applied to the data views and summaries generated by OLAP to provide more in-depth and often more multidimensional knowledge (and predictions). In this sense, Data Mining techniques could be considered to represent either a different analytic approach (serving different purposes than OLAP) or as an analytic extension of OLAP.

For more information on OLAP techniques, see Statistica Interactive Drill-Down Explorer (included in Statistica Data Miner), in particular, the section on Interactive Drill-Down Explorer vs. OLAP.

See also, Data Mining Definition, Data Mining with Statistica Data Miner, Structure and User Interface of Statistica Data Miner, Statistica Data Miner Summary, and Getting Started with Statistica Data Miner.