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An OLAP cube is a multi-dimensional array of data. [1] Online analytical processing (OLAP) [ 2 ] is a computer-based technique of analyzing data to look for insights. 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.
Hierarchy is a dimension hierarchy of a cube. It can be specified by its unique name, e.g. [Time].[Fiscal] or it can be returned by an MDX function, e.g. .Hierarchy. Hierarchies are contained within dimensions. (OLEDB for OLAP MDX specification does not distinguish between dimension and hierarchy data types. Some implementations, such as ...
Multidimensional structure is defined as "a variation of the relational model that uses multidimensional structures to organize data and express the relationships between data". [6]: 177 The structure is broken into cubes and the cubes are able to store and access data within the confines of each cube. "Each cell within a multidimensional ...
A dimension table in an OLAP cube with a star schema. A dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. . Commonly used dimensions are people, products, place and
hierarchical dimensions (attributes that have hierarchical dependencies, such as category-subcategory or country-region) multiple hierarchies in a dimension; arithmetic expressions for computing derived measures and aggregates; localizable metadata and data; Cubes is capable of handling large amounts of data and complex queries.
OLAP systems generally provide for multiple levels of detail within each dimension by arranging the members of each dimension into one or more hierarchies. A time dimension, for example, may be represented as a hierarchy starting with "Total Time", and breaking down into multiple years, then quarters, then months.
Feeding cubes – star schemas are used by all OLAP systems to build proprietary OLAP cubes efficiently; in fact, most major OLAP systems provide a ROLAP mode of operation which can use a star schema directly as a source without building a proprietary cube structure.
Even though it is called a cube (and the examples provided above happen to be 3-dimensional for brevity), a data cube generally is a multi-dimensional concept which can be 1-dimensional, 2-dimensional, 3-dimensional, or higher-dimensional. In any case, every dimension divides data into groups of cells whereas each cell in the cube represents a ...