Abhishek Mehta is the CEO of Tresata, a predictive analytics company redefining business with a deep understanding of customer behavior. Launched in 2011, he has shaped Tresata into one of the most innovative, and fastest growing software companies in the world with a vision to ‘enrich life’.
Abhishek is recognized as one of the most influential thinkers, visionaries, and practitioners in the world of Big Data. He is known both as a radical technology expert and practical, in-the-trenches business leader. His expertise was honed as a known disruptor in classic business and technology roles at Bank of America, Cognizant Technology Solutions and Arthur Andersen and varied academic jaunts at MIT, SRCC & ICAI.
A passionate supporter of entrepreneurship in the SouthEast, Abhishek has been included in numerous lists of the top innovators, leaders and disruptors of our generation. He is a much sought after speaker on the topics of big data analytics, emerging business models and all customary intersections of the two.
About Tresata: Tresata is the leading predictive analytics platform for understanding and monetizing customer behaviors with a singular goal – to enrich lifeTM. This is achieved with great purity, precision, and personalization by Tresata’s analytics engines that have automated the discovery of knowledgeTM from raw data to actionable insight. For more information, visit tresata.com or contact email@example.com
Enterprises commonly collect massive amounts of security related data, such as network logs, as a means of improving security, satisfying compliance regulations, etc. Unfortunately, the potential actionable cybersecurity information within this data goes largely untapped for several reasons including cost, lack of technical ability and understanding for how to approach this data, and a general failure to make security a priority.
The basic premise of Tresata’s approach to intrusion detection expands on the concept of “belief propagation” – that beliefs about who is “good” and who is “bad” travel through a graph over many hops.
Using a distributed approach and our highly scalable graph-based network traversal and discovery software, we apply this premise to isolate the epicenter of machine infections (and other malicious actions) by analyzing network traffic between computers inside our network and servers outside of it.