This course introduces programming techniques used by analysts to transform raw data into a form suitable for predictive modeling. This course uses SAS programming extensively.
Data Preparation for Data Mining
This course assumes some experience in both data mining and SAS programming. Before attending this course, you should
- have experience with common predictive modeling techniques, which you can gain from the Applied Analytics Using SAS Enterprise Miner course
- have experience with creating, managing, and manipulating SAS data sets, which you can gain from the SAS Programming 1: Essentials and SAS Programming 2: Data Manipulation Techniques courses.
Who should attend?
Data mining and IT professionals with SAS DATA step programming experience
- extract relevant data
- transform transactions or event data
- use non-numeric data, including controlling degrees of freedom
- manage exceptions and extremes.
- raw data structures
- predictive modeling data structure
- overview of data preparation challenges
Extracting Relevant Data
- data difficulties
- assessing available data
- accessing available data
- drawing a representative target sample
- drawing an uncontaminated input sample
Transforming Transactions or Event Data
- advantages and disadvantages of transactions data
- common transaction structures
- defining the time horizon
- fixed and variable time horizon methods
- implementing common transaction transformations
Using Non-Numeric Data
- definitions and difficulties of non-numeric data
- miscoding and multicoding detection
- controlling degrees of freedom
Managing Exceptions and Extremes
- difficulties with outliers, missing and non-applicable values, and extreme distributions
- detection of exceptions and extremes
- remedies for exceptional and extreme values
This course addresses Base SAS, SAS/STAT software.
This is a QA approved partner course
Face-to-face learning in the comfort of our quality nationwide centres, with free refreshments and Wi-Fi.
Find dates and prices
Online booking is currently not available for this course, to find out more please call us on 0113 220 7150 or email us at email@example.com to discuss how we can help.
Fully accredited to ensure we provide the highest possible standards in learning