Paul Dorfman is an Independent Consultant. He specializes in developing SAS software solutions from ad hoc programming to building complete data management systems in a range of industries, such as telecom, banking, pharmaceutical, and retail. A native of Ukraine, Paul started using SAS while pursuing his degree in physics in the late 1980's. In 1998, he pioneered using hash algorithms in SAS programming by designing a set of hash routines based on SAS arrays. With the advent of the SAS hash object, Paul was first to use it practically and to author a SUGI white paper on the subject. In the process, he introduced hash object techniques for metadata-based parameter type matching, sorting, unduplication, filtering, data aggregation, dynamic file splitting, and memory usage optimization. Paul has presented papers at global, regional, and local SAS conferences and meetings annually since 1998.
By This Author
Data Management Solutions Using SAS® Hash Table Operations: A Business Intelligence Case Study
Solve your business problems with hash tables and data aggregation. Focusing on real world problems using sports data, this book provides an overview of how hash tables work, as well as the general aggregation philosophies and table look-up narrative at the algorithmic level.
- Marie Gaudard is a consultant specializing in statistical training with the use of JMP. She is currently a statistical writer with the JMP documentation team
- Satish Garla is a former Analytical Consultant in Risk Practice at SAS.
- Sam Gardner is a Senior Research Scientist at Eli Lilly and Company where he is focusing on business analytics and using statistical modeling.