Harsha Rao, Head – Big Data COE at Societe Generale Global Solution Centre on Enabling Intelligence from Big Data
3 Key Takeaways from the Industry Connect Session on 27th October 2018. – 1. What is Big Data?
Big Data is defined not just by a large volume of Data, but also by the variety of the data (for example – social, video, unstructured data) and the velocity of the data. We use Data Science to extract intelligence from Big Data through observational, computational and theoretical research 2. Data Scientists are interdisciplinary
Data scientists have interdisciplinary skill sets, generally in 3 areas – Math & Statistics, Computer skills along with Domain expertise (example – business, marketing, healthcare,etc) which are used to answer specific problems and questions. So for instance one can never be an expert in AI, but an expert for AI in robotics or automated cars and the like. When it comes to Product Managers, answering the “why” part of the problem statement becomes more important, to get insights 3. Traditional Approach Vs. ML
Traditionally, Data Science involved putting forth a problem, with specific hypothesis and then data was derived to feed those to finally get insights for further action. These days with Machine Learning and Big Data, problem definition has become latent and data trends are used to further identify and validate those to get insights and provide suggestive actions.