September 25, 2008 Professional
Development Meeting

* New PD Meeting Location!

Effective with the September Meeting, we will be at the Holiday Inn Select, 1655 N. Central Expressway in Richardson. Click here for a map and visit www.asqdallas.org for additional details and directions.

To register for the meeting, click on the registration link.
Early-Bird Registration ends September 21.

Jami HamptonTutorial and Dinner Speaker: Jami Hampton

Jami Hampton is a JMP Systems Engineer at SAS.  She graduated from Texas A&M University with a BS in Microbiology and a minor in Chemistry.  She worked for 2 years in Microbiology research, for 6 years as an analytical chemist in the beverage industry and for 6 years as a programmer/analyst in the semiconductor industry.  She has worked in software consulting, implementation and training. For the last 10 years, she worked as a software system engineer, primarily in pre-sales.

DINNER TOPIC: Building a Profitable Customer Base:  A Case Study with Data Support

How do we determine how to keep customers happy and coming back for more while still maximizing profit that keeps our shareholders happy?  In this case study, we use data mining and visual data analysis techniques to examine over 200 thousand mobile phone customer information to determine what is most likely to make a customer leave the service provider.  We also determine what customer cohorts are most likely to be profitable so that we can develop the appropriate programs to keep them. Sound complicated?  It's not.  The data and techniques will be easy to understand by anyone who handles customer data, including Six Sigma practitioners.  The techniques shown are also applicable to mining manufacturing data.

TUTORIAL TOPIC : Interactive Data Analysis and Visualization using JMP® Software

Most of us have access to timely information on our desktop about our products, processes and customers. Understanding this information can enable us to build strong and profitable businesses. Accurate analysis is a critical prerequisite to understanding.

In this tutorial, we will demonstrate the use of a widely-used desktop tool, JMP® software from SAS. Built on a powerful set of SAS analytics, JMP uses a menu-driven ‘show-me' paradigm for visual exploratory data analysis. JMP links data, graphics, and statistics to allow you to generate graphical output of your analyses, interrogate your data, filter it on the fly to look at subgroups and examine interesting or problem areas in detail – with just a few mouse clicks and with no programming required. We will use sample data to introduce you to JMP's menu structure, interlinking, and use of contextual analyses that drive you through statistical analyses – even if you are not a statistician.