Dan Zaratsian is a Sr. Solutions Architect with SAS' Global Analytics Practice, specializing in real-time event stream processing, text analytics, and machine learning. He works with a variety of technologies, both open-source and enterprise software, in order to design, program, and implement analytical solutions for clients. Dan holds a M.S. in Analytics from North Carolina State's Institute for Advanced Analytics and a Bachelor’s degree in Electrical Engineering from the University of Akron.
Do you have a need for real-time, streaming analytics? What technology are you considering? How are you going to enable rapid development and deployment of your analytical models all in real-time? SAS has partnered the the Hortonworks HDF team to develop a nifi processor that allows SAS machine learning models and
As technology and analytics continue to evolve, we're seeing new opportunities not only in the way that we analyze data, but also in deployment options. More specifically, real-time deployment of analytical algorithms that enable organizations to detect and respond to security threats, offer timely incentives to customers, and mitigate risk by detecting compliance
Is text analytics part of your current analytical framework? For many SAS customers, the answer is yes, and they've uncovered significant value as a result. As text data continues to explode both in volume and the rate at which it's being generated, SAS Event Stream Processing can be used to
