There is a growing tidal wave of conversation about big data. Anyone who uses data (and also possibly the ones who want to use it) have at least heard about the ‘big-data’ terminology. The data with three V’s, or four V’s or possibly infinity V’s. In the research, analytics and consulting industry, it is now the ‘next cool’ thing to know and apply-quite definitively to generate better, faster and more reliable insights.  In today’s big data world, where we are all becoming too obsessed mastering advanced technologies and sophisticated algorithms and in the course loosening our focus and interest on the art of fundamental research.

Is the data prior to the research objective?

The bottom line of using data, in whatever form it is small/large or big, is broadly to do one of the following: to validate past behaviour or trends, to unearth and triangulate relationships, to forecast or to suggest prescriptive strategies for a unfavourable forecast. However, one should always be cognizant of the one step back of the research process –defining accurately the research objective. Given the nature of big data which we know, is unstructured, ever-increasing and with variety of variables and levels, the key is sticking to the roots of having concrete research plans and objectives before the building those sophisticated algorithm models.This is what particularly I have learnt and tried to diligently practice in my role as a researcher in Re-emerging World.

Quite recently, we completed a socio-economic baseline study for the Jasmine Farming community in the foothills of Niligri range of Coimbatore District, Tamil Nadu for the world’s largest privately owned Swiss company in fragrance and flavours market. At end of base line study, we collected a lot of data points about the socio-economic and farming practices-but as a matter of fact they were all data points. To generate insights and recommendations, I followed the art of research practice i.e. first asking the right fundamental questions, building hypothesis around them, ensuring the data is collected during the study and analysed the data collected to answer those fundamental questions. As in the end, what we all are looking at is the precise answers to our vague questions. And to reach to those answers, we need to master both the art and science of research.

Big Data is an asset which complements and not substitutes research for insights generation

Data has always been an asset in a researcher’s toolbox and big data is a new addition to it. This new asset is all set to transform the way we look, analyse and understand data and will enable to produce better and faster insights which in turn will deliver greater impact and value in the sectors we work. Following the art of research and complementing it with big-data technologies is what will define the next insights imperative.