Data Mining Extensions

Data Mining Extensions(DMX) is aquery languagefordata miningmodels supported byMicrosoft'sSQL Server Analysis Servicesproduct.

LikeSQL,it supports adata definition language(DDL),data manipulation language(DML) and adata query language(DQL), all three with SQL-like syntax. Whereas SQL statements operate on relational tables, DMX statements operate on data mining models. Similarly,Microsoft SQL Serversupports theMDXlanguage forOLAPdatabases. 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.

Queries

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

Data definition language

Thedata 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

Thedata 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]
NATURALPREDICTIONJOIN
(SELECT
35AS[Age],
'Y'AS[House Owner],
'M'AS[Marital Status],
'F'AS[Gender],
2AS[Number Cars Owned],
2AS[Total Children],
18AS[Total Years of Education]
)

See also

• XML for Analysis

External links

• Data Mining Extensions (DMX) Reference,(atMSDN)