In part one of a two-part series, we asked three of our bestselling authors for their favorite papers from SAS Global Forum 2018. Here’s their list:
Ron Cody, author of Learning SAS® Programming by Example, Second Edition, and many more
My first choice is a paper entitled Fuzzy Matching Programming Techniques Using SAS® Software written by Stephen Sloan, Accenture, and Kirk Paul Lafler, Software Intelligence Corporation. This is a topic that I have worked on myself, and this paper lays out a step-by-step approach to matching records from separate files where such items as names and addresses might not be exactly the same. If you find yourself faced with this problem, I strongly recommend that you read this paper.
My next choice might come as a surprise because it discusses a somewhat narrow and esoteric topic. The paper Tips and Techniques for Using Random-Number Generators in SAS®, by Warren Sarle and Rick Wicklin of SAS. This paper is packed with useful and interesting facts about several random-number generators that you can select by using an optional argument in the CALL STREAMINIT routine. This paper discusses the quality of each of the routines, as well as efficiency considerations. I recommend this paper to anyone making extensive use of random numbers. I also recommend Rick Wicklin's book Simulating Data with SAS®.
Kevin Smith, co-author of SAS® Viya®: The Python Perspective and SAS® Viya®: The R Perspective
This paper, Cloud Analytic Services Actions: A Holistic View by Mark Gass, SAS, gives a good introduction to SAS® Cloud Analytic Services (CAS) in general. In addition, it also demonstrates how CAS can be accessed using various clients including Python, R, Java, and SAS.
In my previous life, I did a lot of reporting work that included dealing with styles. Coming up with accessible palettes that still look attractive is always challenging. This poster, Are Color Choices Ruining Your Reports? By Jaime D’Agord, Zencos Consulting LLC, hits on a lot of the most important points to watch out for.
Xiangxiang Meng, co-author of SAS® Viya®: The Python Perspective and SAS® Viya®: The R Perspective
I picked this paper, Image Processing: Seeing the World Through the Eyes of SAS® Viya® by Leigh Ann Herhold and Ivan Gomez, Zencos Consulting LLC , because it provides a great introduction to image analysis and deep learning using facial recognition data. You can learn how to analyze image data through the Python interface of SAS® Viya® in great detail, as well as gain a basic understanding of deep learning for image analysis.
SAS® Enterpriser Miner™ is one of the most popular GUI-based analytical tools developed over the last decade. This paper, Top 10 Tips for SAS® Enterprise Miner™ Based on 20 Years’ Experience, by Melodie Rush, SAS, provides some interesting tips to help you build more robust and accurate pipelines with the software.
If you enjoyed exploring these papers, then check out our free e-book special collections - carefully curated collections of papers around key topics such as machine learning, fraud analytics, SAS® Viya®, the Internet of Things, and more.
Stay tuned for part two, where you’ll hear from three additional SAS Press authors.