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OLAP, or Online Analytical Processing, is a computer technology used to organize large business databases for quick and flexible analysis from multiple perspectives. It helps users analyze data by organizing it into "OLAP Cubes," which allow for multidimensional analysis like slicing, dicing, and pivoting to gain business insights. This is different from OLTP (Online Transaction Processing), which is for daily operational transactions.

Purpose: To support business intelligence and data mining by enabling rapid, multidimensional analysis of large datasets.

Core Concept: Data is structured into a multidimensional model, often called an "OLAP Cube," that groups data by dimensions like time, geography, or products.

Key Operations: OLAP systems support analytical operations such as:

Roll-up: Summarizing data to a higher level (e.g., from months to years).

Drill-down: Moving from a high-level summary to more detailed data (e.g., from countries to cities).

Slice: Creating a sub-cube by selecting a single value for one dimension (e.g., all sales for a specific month).

Dice: Creating a smaller sub-cube by selecting a range of values for multiple dimensions.

Pivot: Rotating the cube's axes to see the data from a different viewpoint.