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Multidimensional Expressions (MDX) is a query language for online analytical processing (OLAP) using a database management system. Much like SQL , it is a query language for OLAP cubes . [ 1 ] It is also a calculation language, with syntax similar to spreadsheet formulae.
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.
The usual interface to manipulate an OLAP cube is a matrix interface, like Pivot tables in a spreadsheet program, which performs projection operations along the dimensions, such as aggregation or averaging. The cube metadata is typically created from a star schema or snowflake schema or fact constellation of tables in a relational database.
As of 2009 two options can export Essbase cubes into other formats: CubePort, a commercial conversion application, converts Essbase cubes to the Microsoft SQL Server Analysis Services product. This product performs an object-to-object translation that make up an Essbase cube, including: outline, member formulas, calc scripts, data loading (load ...
A cube is effectively a function that assigns a value to each n-tuple of the cartesian product of the dimensions. The value of a cell may be assigned externally (input), or the result of a calculation that uses other cells in the same cube or other cubes. The definition of a cube includes the formulas that specify the calculation of such cells.
Data Analysis Expressions (DAX) is the native formula and query language for Microsoft PowerPivot, Power BI Desktop and SQL Server Analysis Services (SSAS) Tabular models. DAX includes some of the functions that are used in Excel formulas with additional functions that are designed to work with relational data and perform dynamic aggregation.
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 ...