NJSUG

NJSUG 2011 Fourth Quarter Meeting

The meeting was in the morning (9:00am - noon) on Friday, Nov 4th at:

Agenda

09:00-09:20	Registration and Continental Breakfast
09:20-10:20	Presentation: Multi-sheet Workbooks from SAS® data using the ODS ExcelXP tagset or Another Way to EXCEL using SAS (Cynthia Stetz)
10:20-10:40	Break
10:40-11:45	Presentation: Predictive Modeling with JMP 9 Pro (Aashish Majethia)
11:45-noon	Door Prize Drawings

Multi-sheet Workbooks from SAS® data using the ODS ExcelXP tagset or Another Way to EXCEL using SAS

Downloads

Paper(pdf) as presented at NESUG 2011

Abstract

Most of us are engaged in providing data to information consumers at least some of the time, and by far the most often requested format is the EXCEL workbook. As the capabilities of Excel have expanded, so have the requests for more and more sophisticated output, and the search for ways to generate this output with the least amount of human effort as possible.

Fortunately, we can rely on the SAS Institute to supply us with innovative tools to make this task easier. One of those tools that I have recently started using to great effect is the ODS ExcelXP tagset. By harnessing some of the vast capabilities available within this tagset, in concert with the judicious application of macro code and Dynamic Data Exchange (DDE), I am now able to deliver nicely formatted, multisheet native Excel workbooks for any number of subsets of my data as might be desired.

Author

Cynthia A. Stetz (Bank of America / Merrill Lynch) has been a SAS programmer since 1990 when a new employer handed her a SAS manual and told her to rewrite a PLI program in SAS. After seeing how powerful the SAS language was she was hooked! Since then she has applied her always expanding SAS skills to provide information delivery solutions to such industries as Insurance, Education and Financial Services. Cynthia holds a BA in Mathematics from Kean University. In her spare time she enjoys recording computer subject matter for the LearningAlly organization (formerly Recording For The Blind and Dyslexic).

Predictive Modeling with JMP 9 Pro

Abstract

JMP Pro is a new product from SAS that helps mining your data like never before. Using push button simplicity, you can build sophisticated models that are easily interpretable. Start taking advantage of your historical data and see long term patterns that you may be missing. With enhanced decision tree algorithms such as bootstrap forest and boosted trees, a new boosted neural nets platform and validation for all of your modeling endeavors, you can take the first step in or your next step in predictive modeling.

As always, JMP is fully integrated with SAS. Once you have developed your models in JMP, it is simple to generate SAS code to run on your existing SAS infrastructure. Run SAS code from within JMP and even mix in JMP code. This integration enables the quick ad hoc analysis of JMP with the scalability and reporting capabilities of SAS. Come see how to enhance your current capabilities using JMP!

Author

Aashish Majethia is a Systems Engineer for JMP, a business unit of SAS specializing in interactive statistical discovery software. Before joining SAS, he worked in business development, engineering and the life sciences. At Raytheon, he developed models and ran simulations of various radar systems. His research experiences span pulmonary physiology, BioMEMS and medical imaging. Majethia earned a Master of Science in biomedical engineering from Boston University and a Bachelor of Science in biomedical engineering from Johns Hopkins University.