Key Objectives and Principles for Building Predictive Models on Big Data (Neustar)

Speaker: Satya Ramachandran, VP of Engineering, Neustar

Presentation: Business analysts spend a lot of time today looking at what happened in the past, but what about trying to grasp what will happen in the future? For example, what if you are given 10 percent more budget for next quarter’s marketing spend? Do you know how you’ll use that extra money, and do you know what impact it will create? Or suppose you want to increase your budget, but need to show what you expect that increase to do – then what? Many of today’s data applications are simply “decision support systems” designed to be useful in the aforementioned scenarios. They help business professionals use data to better understand their environment and make better decisions. But with larger volumes of data and increased ambitions of competitive businesses, the end goals become tougher to achieve. As the VP of Engineering for MarketShare DecisionCloud at Neustar, which provides planning and analytics capabilities for marketers, Satya Ramachandran has taken on these challenges by leveraging big data technologies.

In this talk, Satya will discuss some of the high expectations he’s faced at MarketShare, and also some of his successes. For example, despite the fact that data has grown significantly in recent years, business users still want faster results. This phenomenon led to efforts that supported larger amounts of data within his organization and demanded speed improvements – going from several minutes to sub-second responses. Satya will share some guiding principles that helped him successfully develop and deploy the systems his customers needed to be successful with their big data projects. Learn more about… Data Platforms Conference: Neustar: Qubole: