Explain how to use DMX-the data mining query language.
Data mining extension is based on the syntax of SQL. It is based on relational concepts and mainly used to create and manage the data mining models. DMX comprises of two types of statements: Data definition and Data manipulation.
Data definition is used to define or create new models, structures.
Example:CREATE MINING SRUCTURE
CREATE MINING MODEL
Data manipulation is used to manage the existing models and structures.
Example:INSERT INTO
SELECT FROM .CONTENT (DMX)
Explain how to use DMX-the data mining query language.
DMX – Data mining eXtensions is a language used to work with MS SQL Server Analysis Services.
The following are used for working with DMX:
Data Definition Statements:A mining structure can be created by using the CREATE MINING STRUCTURE statement and it can be dropped by using DROP MINING STRUCTURE
A mining model and associated mining structure can simultaneously be created by using the CREATE MINING MODEL statement and dropped by DROP MINING MODEL
Export a mining model and associated mining structure to a file by using the EXPORT statement
Import a mining model and associated mining structure to a file by using the IMPORT statement
Data Manipulation Statements:A mining model can be trained by using INSERT INTO statement. It creates an abstraction that describes the mining model which the algorithm creates.
To browse the information that is calculated during training model, extend the SELECT statement. The following are the clauses that can be used with SELECT:
SELECT DISTINCT FROM (DMX)
SELECT FROM .CONTENT (DMX)
SELECT FROM .CASES (DMX)
SELECT FROM .SAMPLE_CASES (DMX)
SELECT FROM .DIMENSION_CONTENT (DMX)
