Tài liệu Module 17: Introduction to Data Mining pptx

Contents

Overview 1

Introducing Data Mining 2

Training a Data Mining Model 12

Building a Data Mining Model with

OLAP Data 13

Browsing the Dependency Network 23

Lab A: Creating a Decision Tree with

Relational Data 27

Review 32

Module 17: Introduction

to Data Mining

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY

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Module 17: Introduction to Data Mining iii

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY

Instructor Notes

This module introduces students to data mining and explains how to build and

browse data mining models by using MicrosoftÆ SQL Serverô 2000 Analysis

Services. Students will learn fundamental data mining terminology, concepts,

techniques, and algorithms.

This is an overview module that focuses on the use of built-in Analysis

Manager wizards. It is not intended to provide in-depth knowledge of data

mining.

After completing this module, students will be able to:

! Describe data mining characteristics, applications, and modeling techniques.

! Describe the process of training a model.

! Use the online analytical processing (OLAP) Mining Model Wizard to edit,

process, and explore the decision trees.

! Analyze relational data relationships in the dependency network browser.

! Describe the steps required to build a clustering model by using OLAP data.

Materials and Preparation

This section lists the required materials and preparation tasks that you need to

teach this module.

Required Materials

To teach this module, you need Microsoft PowerPointÆ file 2074A_17.ppt.

Preparation Tasks

To prepare for this module, you should:

! Read all the materials for this module.

! Read the instructor notes and margin notes.

! Practice combining the lecture with the demonstrations.

! Complete the lab.

! Review the Trainer Preparation presentation for this module on the Trainer

Materials compact disc.

! Review any relevant white papers that are located on the Trainer Materials

compact disc.

Presentation:

40 Minutes

Lab:

20 Minutes

iv Module 17: Introduction to Data Mining

BETA MATERIALS FOR MICROSOFT CERTIFIED TRAINER PREPARATION PURPOSES ONLY

Demonstration: Determining Why Students Attend College

The following demonstration procedures provide information that will not fit

in the margin notes or is not appropriate for student notes.

In this demonstration, you will create a data mining model by using a decision

tree with relational data. Specifically, you will create a decision tree that

determines why students attend college.

You will create a new OLAP database with a data source connecting to the

Module 17 relational database.

! To create an OLAP database

1. In Analysis Manager, expand the Analysis Servers folder, right-click your

local server, and then click New Database.

2. Enter Module 17 as the database name, and then click OK.

3. Expand the Module 17 database, right-click the Data Sources folder, and

then click New Data Source.

4. On the Provider tab of the Data Link Properties dialog box, click

Microsoft OLE DB Provider for SQL Server. Click Next.

5. Type localhost in Step 1.

6. In Step 2, click Use Windows NT Integrated security.

7. In Step 3, click Module 17 from the list of databases. Click OK.

! To create the data mining model

In this procedure, you will create the data mining model by selecting source,

case table, data mining technique, and key column.

1. In the Module 17 database, right-click the Mining Models folder, and then

click New Mining Model.

2. At the welcome page, click Next.

3. From the Select source type step of the Mining Model Wizard, click

Relational data, and then click Next.

Point out that either relational tables or OLAP cubes can be used as source

data. For this model, you are accessing relational data.

4. From the Select case tables step, in the Available tables list, click College

Plans, and then click Next.

5. From the Select data mining technique step, in the Technique list, click

Microsoft Decision Trees, and then click Next.

Two algorithms ship with Analysis Services: Microsoft Decision Trees and

Microsoft Clustering. Use the Decision Trees algorithm for this

demonstration.

6. From the Select the key column step, in the Case key column list, click

StudentID, and then click Next.

Demonstration:

10 Minutes