Page 183 - DCAP606_BUSINESS_INTELLIGENCE

Business Intelligence Sarabjit Kumar, Lovely Professional University

Notes Unit 13: Creating Data Mining Queries and Reports

CONTENTS
Objectives
Introduction

13.1 Prediction Queries
13.1.1 Basic Prediction Query Design
13.1.2 Adding Prediction Functions

13.1.3 Singleton Query
13.1.4 To Create a Singleton Prediction Query
13.1.5 Batch Query
13.2 Data Mining Extensions (DMX)
13.2.1 DMX Statements

13.2.2 Data Definition Statements
13.2.3 Data Manipulation Statements
13.2.4 DMX Query Fundamentals

13.3 Summary
13.4 Keywords
13.5 Review Questions
13.6 Further Readings

Objectives

After studying this unit, you will be able to:

Explain prediction queries
Discuss about data mining extensions

Introduction

Data Mining Extensions (DMX) is a query language used 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. Difference
is that SQL statements operate on relational tables while DMX statements operate on data
mining models. In this unit, you will learn about prediction queries like adding, singleton and
batch queries. Later on in this unit you will learn about data mining extensions and statements-
data definition statements, data manipulation statements and data query statements.

13.1 Prediction Queries

The aim of a usual data mining task is to use the mining model to make predictions.

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