Exploratory Analysis for Large and Complex Problems Using SAS Enterprise Miner
Business Knowledge Series course
Presented by Jeff Zeanah, President of Z Solutions, Inc..
This course is intended for analysts working with virtually any type of exploratory data analysis problem. Discovery in a complicated data set is one of the analyst's toughest problems. The course covers this discovery process using many real-world problems. There is a focus on fraud detection, with the recognition that the core principles of modeling to solve fraud detection are the basis of all exploratory data analysis. Analytical methods used in the course include decision trees, logistic regression, neural networks, link analysis, and social network analysis. In addition, analysts receive practical advice on presenting complex findings to their audience.
Learn how to
Who should attendData analysts (market researchers, fraud researchers, and sales analysts); expert modelers or those who want to become expert; and the creative and curious
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To maximize the return on investment from the class, you should have the following skills and experience:
This class is taught in SAS Enterprise Miner and foundation SAS. Familiarity with SAS Enterprise Miner at the level presented in the Applied Analytics Using SAS Enterprise Miner course is helpful. Most of the techniques shown in this course using SAS Enterprise Miner are supplemented with similar approaches in foundation SAS.
This course addresses SAS Enterprise Miner software.
Predictive Analytics and Exploratory Data Mining