View source for Multidimensional Expressions (MDX)

'''Multidimensional Expressions (MDX)''' is a query language designed for querying and manipulating multidimensional data stored in Online Analytical Processing (OLAP) databases, such as SQL Server Analysis Services and Oracle's Essbase. MDX was developed by Microsoft in the late 1990s and has since become an industry standard for working with OLAP cubes.

== Purpose and Role ==
The primary purpose of MDX is to enable users to extract meaningful information from large amounts of multidimensional data stored in OLAP databases. MDX allows users to perform operations such as slicing and dicing, drilling up and down, pivoting, filtering, and aggregating data to gain insights and make informed business decisions.

== Components ==
MDX has several key components, including:

*'''Dimensions:''' Dimensions are the categories that data is organized by within a multidimensional data model, such as time, geography, product, or customer.

*'''Measures:''' Measures are the numerical values associated with dimensions, such as sales, revenue, or profit.

*'''Members:''' Members are the individual elements within a dimension, such as specific years, products, or regions.

*'''Tuples:''' Tuples are ordered sets of members from different dimensions, representing a specific data point in the OLAP cube.

*'''Sets:''' Sets are unordered collections of tuples or members, used for grouping and filtering data in MDX queries.

== Importance ==
MDX is an essential tool for business analysts, data scientists, and other professionals who need to analyze and report on multidimensional data. By using MDX, users can:

*Access and analyze data from OLAP databases efficiently.
*Perform complex calculations and aggregations on multidimensional data.
*Create custom reports and visualizations that reveal hidden patterns and trends.
*Improve decision-making by providing actionable insights based on data analysis.

== Example ==
Consider a simple MDX query to retrieve the total sales amount for each product category and year from an OLAP cube:

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SELECT
  {[Measures].[Sales Amount]} ON COLUMNS,
  NON EMPTY CROSSJOIN(
*{[Product].[Category].Members},
*{[Date].[Year].Members}
  ) ON ROWS
FROM [Sales]

This query selects the "Sales Amount" measure, retrieves product categories and years, and returns the sales amount for each combination of product category and year.

In summary, Multidimensional Expressions (MDX) is a powerful query language for working with multidimensional data in OLAP databases. It allows users to extract insights from large amounts of data and supports complex calculations and aggregations. MDX is an essential tool for business analysts, data scientists, and other professionals who need to analyze and report on multidimensional data.










== See Also ==
*[[IT Strategy (Information Technology Strategy)]]
*[[IT Governance]]
*[[Enterprise Architecture]]
*[[Chief Information Officer (CIO)]]
*[[IT Sourcing (Information Technology Sourcing)]]
*[[IT Operations (Information Technology Operations)]]
*[[E-Strategy]]






== References ==
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