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Data Mining Extensions (DMX) is a query language for data mining models supported by Microsoft's SQL Server Analysis Services product.[1]

Like SQL, it supports a data definition language, data manipulation language and a data query language, all three with SQL-like syntax. Whereas SQL statements operate on relational tables, DMX statements operate on data mining models. Similarly, SQL Server supports the MDX language for OLAP databases. DMX is used to create and train data mining models, and to browse, manage, and predict against them. DMX is composed of data definition language (DDL) statements, data manipulation language (DML) statements, and functions and operators.


DMX Queries are formulated using the SELECT statement. They can extract information from existing data mining models in various ways.

Data definition language

The data definition language (DDL) part of DMX can be used to

Data manipulation language

The data manipulation language (DML) part of DMX can be used to

Example: a prediction query

This example is a singleton prediction query, which predicts for the given customer whether she will be interested in home loan products.

  [Loan Seeker],
  PredictProbability([Loan Seeker])
  [Decision Tree]
   35 AS [Age],
   'Y' AS [House Owner],
   'M' AS [Marital Status],
   'F' AS [Gender],
   2 AS [Number Cars Owned],
   2 AS [Total Children],
   18 AS [Total Years of Education]

See also


  1. ^ "Sql server - Explain how to use DMX-the data mining query language". Retrieved 2022-08-23.