Data Mining Extensions
Encyclopedia
Data Mining Extensions 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.
They can extract information from existing data mining models in various ways.
(DDL) part of DMX can be used to
Data mining
Data mining , a relatively young and interdisciplinary field of computer science is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems...
Models supported by Microsoft
Microsoft
Microsoft Corporation is an American public multinational corporation headquartered in Redmond, Washington, USA that develops, manufactures, licenses, and supports a wide range of products and services predominantly related to computing through its various product divisions...
'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
Multidimensional Expressions
Multidimensional Expressions is a query language for OLAP databases, much like SQL is a query language for relational databases. It is also a calculation language, with syntax similar to spreadsheet formulas.-Background:...
language for OLAP
OLAP
In computing, online analytical processing, or OLAP , is an approach to swiftly answer multi-dimensional analytical queries. OLAP is part of the broader category of business intelligence, which also encompasses relational reporting and data mining...
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
DMX Queries are formulated using theSELECT statement.They can extract information from existing data mining models in various ways.
Data Definition Language
The Data Definition LanguageData Definition Language
A data definition language or data description language is a syntax similar to a computer programming language for defining data structures, especially database schemas.-History:...
(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]
)