Parent elements can further be aggregated as the children of another parent. The elements of a dimension can be organized as a hierarchy, a set of parent-child relationships, typically where a parent member summarizes its children. Measures are derived from the records in the fact table and dimensions are derived from the dimension tables. OLAP data is typically stored in a star schema or snowflake schema in a relational data warehouse or in a special-purpose data management system. Spreadsheets are only 2-dimensional, so by (continued) slicing or other techniques, it becomes possible to visualise multidimensional data in them.Įach cell of the cube holds a number that represents some measure of the business, such as sales, profits, expenses, budget and forecast. But this term is used widely.Ī Slice is a term for a subset of the data, generated by picking a value for one dimension and only showing the data for that value (for instance only the data at one point in time). A cube is not a 'cube' in the strict mathematical sense, as the sides are not all necessarily equal. The term hypercube is sometimes used, especially for data with more than three dimensions. Ĭube is a shorthand for multidimensional dataset, given that data can have an arbitrary number of dimensions. Product, time, city and scenario (actual and budget) are the data's dimensions. For example, a company might wish to summarize financial data by product, by time-period, and by city to compare actual and budget expenses. The term cube here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three.Ī cube can be considered a multi-dimensional generalization of a two- or three-dimensional spreadsheet. Online analytical processing (OLAP) is a computer-based technique of analyzing data to look for insights. An OLAP cube is a multi-dimensional array of data.

Hypercube rotation