Predictive Analytics for Networks

The Network is a living, breathing ecosystem, ripe to be mined, read and analyzed. There are a lot of systems today that analyze and mine large volumes of static data and find trends, patterns and predictions. Real-time traffic and data takes it to a whole new level. The challenge for Data Scientists and Statisticians takes it up several notches and makes it even more exciting when they have to come up with real-time pattern mining and analysis, with a high degree of accuracy & confidence-levels and real-time predictions – just in time to trigger a real-time preemption. This session talks about the challenges, the models and use-cases. How Networks can become highly intelligent & self-adapting – through real-time machine-learning applying combination of batch insights & real-time insights to real-time predictions.

Gargi Adhav is the Director of Analytics of Cisco and has been the founder of 2 startups in the Mobile Location-based Analytics & Social Recommendation Engines. Her expertise spans over Network Intelligence, Routing, Switching, Forwarding, Machine Learning, BigData and Social Analytics. Author of 26 patent submissions and numerous Internet drafts, she has been a pioneer in Network Convergence, Non-stop Routing, Multi-Topology Routing and Multicast VPNs.