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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.
XML for Analysis (XMLA) is an industry standard for data access in analytical systems, such as online analytical processing (OLAP) and data mining. XMLA is based on other industry standards such as XML, SOAP and HTTP. XMLA is maintained by XMLA Council with Microsoft, Hyperion and SAS Institute being the XMLA Council founder members.
OLAP clients include many spreadsheet programs like Excel, web application, SQL, dashboard tools, etc. Many clients support interactive data exploration where users select dimensions and measures of interest. Some dimensions are used as filters (for slicing and dicing the data) while others are selected as the axes of a pivot table or pivot chart.
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.
A common data warehouse example involves sales as the measure, with customer and product as dimensions. In each sale a customer buys a product. The data can be sliced by removing all customers except for a group under study, and then diced by grouping by product. A dimensional data element is similar to a categorical variable in statistics.
TM1 Web/TM1 Contributor, IBM Cognos Insight, IBM Performance Modeler, IBM Cognos Cafe for Excel, Cognos BI, TM1 Perspectives for Excel Yes Yes icCube Yes Yes Yes Java, [23] R [24] Yes In the reporting Yes icCube reporting and all XMLA compliant visualization tools like Excel, etc Yes Yes Jedox OLAP Server: Yes Yes Yes Cube Rules, SVS Triggers ...
In 1996, Ralph Kimball, who is widely regarded as one of the original architects of data warehousing, stated: [3] The single most dramatic way to affect performance in a large data warehouse is to provide a proper set of aggregate (summary) records that coexist with the primary base records.
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.