Logical Architecture (Analysis Services - Multidimensional Data)

Designing and Implementing (Analysis Services - Data Mining)

See Also

Working with Data Mining

Microsoft SQL Server Data Mining resources

Creating and Querying Data Mining Models with DMX: Tutorials (Analysis Services - Data Mining)

Basic Data Mining Tutorial

Welcome to the Microsoft Analysis Services Basic Data Mining Tutorial. Microsoft SQL Server provides an integrated environment for creating and working with data mining models. In this tutorial, you will complete a scenario for a targeted mailing campaign in which you create models for analyzing and predicting customer purchasing behavior and for targeting potential buyers. The tutorial demonstrates how to use three of the most important data mining algorithms, how to analyze your findings using the mining model viewers, create predictions and accuracy charts, using the data mining tools that are included in Microsoft SQL Server Analysis Services. The fictitious company, Adventure Works Cycles, is used for all examples.

When you are comfortable using the data mining tools, we recommend that you also complete the Intermediate Data Mining Tutorial, which demonstrates how to use forecasting, market basket analysis, time series, association models, nested tables, and sequence clustering.

Tutorial Scenario

In this tutorial, you are an employee of Adventure Works Cycles who has been tasked with learning more about the company's customers based on historical purchases, and then using that historical data to make predictions that can be used in marketing. The company has never done data mining before, so you must create a new database specifically for data mining and set up several data mining models.

What You Will Learn

This tutorial teaches you how to create and work with several different types of data mining models. It also teaches you how to create a copy of a mining model, and apply a filter to the mining model. You then process the new model and evaluate the model using a lift chart. After the model is complete, you use drillthrough to retrieve additional data from the underlying mining structure.

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Microsoft Analysis Services Data Mining includes the following features that help you easily develop and compare multiple predictive models and then take actions on the results :

•Holdout Test Sets - When you create a mining structure, you can now divide the data in the mining structure into training and testing sets. This lets you test models on similar data sets, and compare the accuracy of related models.

•Mining model filters - You can now attach filters to a mining model, and apply the filter during both training and testing. This lets you easily build related models on different subsets of the data.

•Drillthrough to Structure Cases and Structure Columns - You can now easily move from the general patterns in the mining model to actionable detail in the data source.

This tutorial is divided into the following lessons:

Lesson 1: Preparing the Analysis Services Database

In this lesson, you will learn how to create a new Analysis Services database, add a data source and data source view, and prepare the new database to be used with data mining.

Lesson 2: Building the Targeted Mailing Scenario

In this lesson, you will learn how to create a mining model structure that can be used as part of a targeted mailing scenario.

Lesson 3: Adding and Processing Models

In this lesson you will learn how to add models to a structure. The models you create are built with the following algorithms:

•Microsoft Decision Trees

•Microsoft Clustering

•Microsoft Naive Bayes

Lesson 4: Exploring the Targeted Mailing Models (Basic Data Mining Tutorial)

In this lesson you will learn how to explore and interpret the findings of each model using the Viewers.

Lesson 5: Testing Models (Basic Data Mining Tutorial)

In this lesson, you make a copy of one of the targeted mailing models, add a mining model filter to restrict the training data to a particular set of customers, and then assess the viability of the model.

Lesson 6: Creating and Working with Predictions (Basic Data Mining Tutorial)

In this final lesson of the Basic Data Mining Tutorial, you use the model to predict which

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