5.4.2 - In-Database Analytic Functions - Teradata Warehouse Miner

In-Database Analytic Functions User Guide

prodname
Teradata Warehouse Miner
vrm_release
5.4.2
created_date
October 2016
category
User Guide
featnum
B035-2306-106K

This document describes a number of in-database analytic functions that may be invoked from any Teradata SQL query execution product, such as Teradata Studio or Teradata Bteq. The controlling program for these analytic functions is a custom Teradata External Stored Procedure called TD_Analyze. Some of the functions also utilize custom Teradata Table Operators. In order to use the Teradata Warehouse Miner In-Database Analytic Functions, these user-defined functions must be installed in the Teradata database using a console application supplied with the Teradata Warehouse Miner product, accessible from the client Start menu in the Teradata Warehouse Miner program group. Once these user-defined functions are installed, the functions described in this document can be executed without the need to invoke the Teradata Warehouse Miner client application.

Although independent of the Teradata Warehouse Miner client application, the in-database analytic functions described in this document are based on functions available in that product. In fact, all of the in-database functions and more are provided in the Teradata Warehouse Miner client application, which has three principal function categories.

Function Category Description
Data Profiling Descriptive statistics provided to generate reports and graphics with drill down capabilities, pointing out potential data quality issues. The In-Database Descriptive Statistics functions described in this document are derived from the corresponding functions in the Data Profiling function category.
Analytic Data Set (ADS) Generation Functions used to build and transform analytic data sets. The In-Database Variable Transformation function described in this document is derived from the Variable Transformation function in the Analytic Data Set Generation function category.
Analytic Functions Functions used to build analytic algorithms and scoring along with statistical tests. In this document, the In-Database Fast K-Means algorithm and the Gain Ratio Extreme algorithm provide new variations of the Clustering and Decision Tree algorithms and scoring in Teradata Warehouse Miner in the Analytic Functions category.

Like all of the in-database functions described in this document, these new variations are also provided in the Teradata Warehouse Miner client application. When accessed there, you can make use of the graphing and reporting capabilities available there.

The examples in this document can be copied and used on a system where the UDF has been installed and the twm default user name along with the rest of the tutorial environment (including the twm_source, the twm_result database, and the tutorial tables installed in twm_source) has been set up.