Once you've installed the Evaluation Copy of Teradata Warehouse Miner (described in the article "Getting Started Installing and Configuring Teradata Warehouse Miner"), there are now two ways to get to know Teradata Warehouse Miner. First, you can get started quickly by loading and viewing a supplied tutorial project. Second, you can learn how to build a project from scratch, with specific examples in on the following:
To create a new project and step through the demo below, click on the Add New Project icon on the toolbar or select File >> Add New Project on the main menu.
A Histogram analysis is designed to study the distribution of continuous numeric values in columns. It’s often referred to as “binning” because it counts the occurrence of values in a series of numeric ranges called “bins”.
Scatter plots are useful to identify relationships and outliers across two and/or three different variable combinations.
Teradata Warehouse Miner provides decision trees for classification and regression models to predict an outcome (dependent variable) based on many predictors (independent variables). In this example, we’re going to use a decision tree analysis to predict credit card ownership.
After building a Decision Tree model with Teradata Warehouse Miner, you can create a score table based on that model.
If you want to view the scoring SQL, now perform the following: