A data cube is a multi-dimensional array of values used to represent data along some dimensions of interest. It is a data structure that can store data in more than two dimensions, unlike tables and spreadsheets. The data cube is used to represent data (sometimes called facts) along some dimensions of interest. For example, in online analytical processing (OLAP), such dimensions could be the subsidiaries a company has, the products the company offers, and time; in this setup, a fact would be a sales event where a particular product has been sold in a particular subsidiary at a particular time.

Data cubes are mainly used for business intelligence and decision support systems. They are optimized for fast and efficient analysis, enabling users to consolidate or aggregate relevant data into the cube and then drill down, slice and dice, or pivot data to view it from different angles. Data cubes are characterized by their dimensions, which are associated with corresponding attributes. For example, the attributes of the Products dimension could be T-Shirt, Shirt, Jeans, and Jackets.

Data cube operations are used to manipulate data to meet the needs of users. These operations help to select particular data for the analysis purpose. There are mainly five operations: rollup, drill-down, slicing, dicing, and pivoting. Data cubes enable multi-dimensional analysis of business data, allowing users to view data from different perspectives and levels of detail. They provide interactive access to large amounts of data, allowing users to easily navigate and manipulate the data to support their analysis. Data cubes are optimized for OLAP analysis, enabling fast and efficient querying and aggregation of data.