Getting Started With

Getting Started with

Enterprise Miner

Software

From SAS On-line Tutorial

Welcome to the Enterprise Miner Tutorial
Introduction
Start here. You will get an overview of data mining and Enterprise Miner, as well as the scenario behind this tutorial.
Dig for diamonds with Enterprise Miner [pages 4-5]
Define the business problem [pages 6]
Accessing Data
Enterprise Miner relies on data from outside sources, so you need to tell it where to find your data set, data warehouse, or table.
Create a new project [pages 7-12]
Explore data [pages 13-15]
Preparing Data
At the heart of data mining is data preparation, which can improve the power of your model. You will adjust metadata, clean up the training data, and create a target variable.
Transform variables [pages 16-17]
Modify attributes [pages 18-23]
Define target profile [pages 24-29]
Partition data [pages 31-32]
Replace data [pages 33-35]
Modeling/Assessing: Regression
Modeling is quick and easy. You will set up and run a regression model, and then see how well it predicts the target.
Build regression model [pages 36-40]
Assess regression model [pages 41-44]
Modeling/Assessing: Decision Tree
Enterprise Miner can run multiple models and compare their results. You will create a decision tree and see how it compares to regression.
Build decision tree model [pages 45-51]
Assess decision tree model [pages 52-56]
Reporting/Scoring
After you have picked the best model, you need to apply it to data. Here are two methods, one of which you can run with base SAS.
Create HTML report [page 57]
Create score code [pages 58-69]
Conclusion
You have mastered the essentials, but there is much more to Enterprise Miner. Check this overview of other nodes and resources.
Additional nodes and resources [pages 70-71]

Getting Started with Enterprise Miner

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