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An example of an OLAP cube. 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.
In computer programming contexts, a data cube (or datacube) is a multi-dimensional ("n-D") array of values. Typically, the term data cube is applied in contexts where these arrays are massively larger than the hosting computer's main memory; examples include multi-terabyte/petabyte data warehouses and time series of image data.
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.
Editor Kenny MacIver said: "Hyperion Essbase was the multi-dimensional database technology that put online analytical processing on the business intelligence map. It has spurred the creation of scores of rival OLAP products – and billions of OLAP cubes". [6]
Cubes provides to an analyst or any application end-user "understandable and natural way of reporting using concept of data Cubes – multidimensional data objects". Cubes was first publicly released in March 2011. The project was originally developed for Public Procurements of Slovakia. [3]
The functional model is based on multidimensional arrays, or "cubes", of cells that, as in a spreadsheet, can be either externally input, or calculated in terms of other cells. Such cubes are constructed using dimensions which correspond to hierarchically organized sets of real entities such as products, geographies, time, etc.
The MultiDimensional eXpressions (MDX) language provides a specialized syntax for querying and manipulating the multidimensional data stored in OLAP cubes. [1] While it is possible to translate some of these into traditional SQL, it would frequently require the synthesis of clumsy SQL expressions even for very simple MDX expressions.
In statistics, econometrics and related fields, multidimensional analysis (MDA) is a data analysis process that groups data into two categories: data dimensions and measurements. For example, a data set consisting of the number of wins for a single football team at each of several years is a single-dimensional (in this case, longitudinal) data ...