Data Mining Extensions

Data Mining Extensions (DMX) is a query language for Data Mining Models supported by Microsoft's SQL Server Analysis Services product.

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.

Contents 1 DMX Queries 2 Data Definition Language 3 Data Manipulation Language 4 Example: a prediction query 5 See also 6 External links

DMX Queries

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

• Create new data mining models and mining structures - CREATE MINING STRUCTURE, CREATE MINING MODEL
• Delete existing data mining models and mining structures - DROP MINING STRUCTURE, DROP MINING MODEL
• Export and import mining structures - EXPORT, IMPORT
• Copy data from one mining model to another - SELECT INTO

Data Manipulation Language

The Data Manipulation Language (DML) part of DMX can be used to

• Train mining models - INSERT INTO
• Browse data in mining models - SELECT FROM
• Make predictions using mining model - SELECT ... FROM PREDICTION JOIN

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.

SELECT
  [Loan Seeker],
  PredictProbability([Loan Seeker])
FROM
  [Decision Tree]
NATURAL PREDICTION JOIN
(SELECT 
   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

• XML for Analysis

External links

• Data Mining Extensions (DMX) Reference, (at MSDN)
• SQL Server Data Mining
• Jamie MacLennan's Blog

Data warehouse Creating the data warehouse Concepts Database Dimension Dimensional modeling Fact OLAP Star schema Aggregate Variants Anchor Modeling Column-oriented DBMS Data Vault Modeling HOLAP MOLAP ROLAP Operational data store Elements Data dictionary/Metadata Data mart Sixth normal form Surrogate key Fact Fact table Early-arriving fact Measure Dimension Dimension table Degenerate Slowly changing Filling Extract-Transform-Load (ETL) Extract Transform Load Using the data warehouse Concepts Business intelligence Dashboard Data mining Decision support system (DSS) OLAP cube Languages Data Mining Extensions (DMX) MultiDimensional eXpressions (MDX) XML for Analysis (XMLA) Tools Business intelligence tools Reporting software Spreadsheet Related People Bill Inmon Ralph Kimball Products Comparison of OLAP Servers Data warehousing products and their producers

Query languages .QL CQL CODASYL COQL D DMX Datalog ISBL LDAP MQL MDX OQL OCL Poliqarp Query Language QUEL SMARTS SPARQL SQL SuprTool TMQL XQuery XPath YQL