With the limitations that of Online Transaction Processing, or OLTP, businesses today are looking for a faster and more effective way to consolidate and make sense of data that is created each day.

OLTP is a class of programs that facilitates and manages transaction-oriented applications, typically for data entry and retrieval transactions. Performing such tasks as queries with OLTP can often be both time-consuming and non-intuitive.

Gaining access to key information from data in order to make timely business decisions requires scalable structures and quick and easy processes to be in place.

Online Analytical Processing, or OLAP, is a technology that uses multidimensional structures to provide rapid data access for analysis. The source data for OLAP is commonly stored in data warehouses or in a relational database.

OLAP is implemented in a multi-user client/server mode and offers rapid response to queries, regardless of the size and complexity of a database. OLAP enables businesses to merge raw information together for comparative and personalized viewing, as well as for the analysis of historical and projected data.

OLAP functionality is characterized by its ability to consolidate business data to allow dynamic multi-dimensional analysis including:

• Calculations and modeling applied across dimensions, through hierarchies and/or across members;
• Trend analysis over sequential time periods.

All in all, OLAP enables analysts, managers, and executives to gain insight into data through fast and interactive access to a wide variety of segmented information.