which one should be used to accomplish the tasks above?

You are a database developer and you have about two years experience in creating business intelligence (BI) solutions by using SQL Server2008.

Now you are employed in a company which is named NaproStar and work as the technical support for the company which uses SQL Server2008 Analysis Services (SSAS).
To meet the business development, (SSAS) is used to create a data mining model and the Data Mining Extensions (DMX) code is used to create a mining structure.

The Data Mining Extensions (DMX) code is shown as the following:

Now you are assigned the following tasks:
Make sure that the Microsoft Decision Trees algorithm is used by the model. Have a mining model that can be processed by this mining structure created.

So of the following DMX statements, which one should be used to accomplish the tasks above? (Exhibit)

You are a database developer and you have about two years experience in creating business intelligence (BI) solutions by using SQL Server2008.

Now you are employed in a company which is named NaproStar and work as the technical support for the company which uses SQL Server2008 Analysis Services (SSAS).
To meet the business development, (SSAS) is used to create a data mining model and the Data Mining Extensions (DMX) code is used to create a mining structure.

The Data Mining Extensions (DMX) code is shown as the following:

Now you are assigned the following tasks:
Make sure that the Microsoft Decision Trees algorithm is used by the model. Have a mining model that can be processed by this mining structure created.

So of the following DMX statements, which one should be used to accomplish the tasks above?

A.
INSERT INTO [Decision Tree] ( [Customer Key], [Age], [Bike Buyer], [Commute Distance], [Yearly Income])OPENQUERY([Bike Buyer], ‘Select [Customer Key], [Age], [Bike Buyer] , [Commute Distance],[Yearly Income]’)

B.
SELECT * INTO [Decision Tree]USING [Microsoft_Decision_Trees]FROM [Bike Buyer]

C.
CREATE MINING MODEL [Decision Tree] ( [Customer Key] LONG KEY, [Age] LONG DISCRETIZED(Automatic, 10), [Bike Buyer] LONG DISCRETE, [Commute Distance] TEXT DISCRETE, [Yearly Income] DOUBLE CONTINUOUS) USING Microsoft_Decision_Trees

D.
ALTER MINING STRUCTURE [Bike Buyer]ADD MINING MODEL [Decision Tree] ( [Customer Key], [Age], [Bike Buyer] PREDICT, [Commute Distance], [Yearly Income]) USING Microsoft_Decision_TreesWITH DRILLTHROUGH

Explanation:
Exam D



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