Exploratory Analysis for Large and Complex Problems

Business Knowledge Series course

This course is not currently scheduled.

Duration: 3.0 days
Course fee:
EPTO units: .
CEUs: 1.8

Presented by Jeff Zeanah, President of Z Solutions, Inc.

This course presents perspective-changing combinations of graphics and predictive analytics in a framework that addresses the realities that an analytical staff faces in developing and presenting new exploratory findings. Complex exploratory predictive models are built with real-world data and investigated.

Learn how to

use new methods to screen data sets with large numbers of variables
use new graphical techniques to present findings
find hidden relationships in multiple dimensions.

Who should attend

Data analysts who support tasks such as market research, sales analysis and forecasting, list mining, R&D, and process improvement

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Prerequisites

To maximize the return on investment from the class, you should have the following skills and experience:

background in analytical methods
experience with predictive modeling
familiarity with Base SAS, SAS/STAT, and SAS/GRAPH software, which you can acquire by taking the SAS Programming I: Essentials or Statistics I: Introduction to ANOVA, Regression, and Logistic Regression course.

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 5 course is helpful. Most of the techniques shown in this course using SAS Enterprise Miner are supplemented with similar approaches in foundation SAS.

Course Contents

Predictive Analytics and Exploratory Data Mining

the relationship between predictive analytics and exploratory data mining
the role of graphics in exploratory analysis
complexity in a PowerPoint world
the analyst's dilemma

Working with Unstructured Data

data streams versus structured data
social network analysis as a solution to unstructured problems
statistical mechanics of network analyses
predicting with a network
complex networks versus reductionism

Exploratory Data Mining and Predictive Models

exploratory data mining success
predictive modeling methods
logistic regression
decision trees
neural networks
the truth about neural networks
comparing and contrasting predictive modeling methods
model structure and impact on exploratory results
graphical review of model results
multi-dimensional graphics

Exploratory Predictive Modeling

initial data screening
elements of an exploratory script
developing complex predictive models for exploratory efforts
identifying important variables
analyzing variables, domains, and clusters
graphical review of models and data

Exploratory Findings

extracting new hypotheses (exploratory findings) from the predictive model
building confidence with the exploratory findings
recognizing and overcoming impediments to acceptance by the target audience

Software

This course addresses SAS Enterprise Miner, SAS/STAT.

Course Materials

Students receive a hardcopy of the course notes and, in some courses, can choose to take home a copy of the course data.

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Are there additional topics you'd like for this course to address? Would you like for this course to be offered at another training facility? Let us know by adding to our Interest List.

Course fee and EPTO units will differ for on-site training.

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