BIG DATA WILL CHANGE THE WAY BUSINESS IS DONE Date:   Friday , June 01, 2012 Suarabh Suri, Senior Director, Solutions & Services, Big Data & Predictive Analytics at UST believes the biggest markets in India for Big Data Analytics would be government, B2C and Financial sectors. In a candid chat, he talks about the trends, opportunities and challenges that Big Data is bringing in. Trends in Big Data There is huge data boom happening today. Years ago, terabytes of data was hard to get but today the same can be collected in a matter of days. And this data generation is happening from all over the flex. Its not the organizations alones but with Internet, Social Networking and connected devices, data boom is beyond anyone’s imagination. Today, it is all about Big Data. Although it has been of critical use to tech giants such as Google, Yahoo! and Facebook for number of years now, it is only now that it is permeating into enterprises or the business domain. As per a study by McKinsey, a retailer using big data to the full could increase its operating margin by more than 60 percent. Harnessing big data in the public sector has enormous potential, too. If U.S. healthcare were to use big data creatively and effectively to drive efficiency and quality, the sector could create more than $300 billion in value every year. Two-thirds of that would be in the form of reducing U.S. healthcare expenditure by about 8 percent. In the developed economies of Europe, government administrators could save more than $149 billion in operational efficiency improvements alone by using big data, not including using big data to reduce fraud and errors and boost the collection of tax revenues. And users of services enabled by personal-location data could capture $600 billion in consumer surplus. Similarly, five years ago if I wanted to mash and process the terabytes of data in different velocities, some in real time and some in near time, would have to spend millions of dollars in terms of infrastructure, licenses and others. Now with commoditized hardware and thanks to the cloud and cloud computing along with open source software Hadoop, it has become financially viable to process the ridiculously large amount of data. Because of the commoditization of the hardware and the falling cost of having the ability to parcel this kind of data, we see small and medium businesses adapt and adopt this technology quickly and challenge the established players. And that has bound the industry into itself, both in terms of end products to consumers, and in terms of services the people are provided leveraging the big data and the analytics that sit on top of big data. Earlier Indian IT service providers were to provide value to the IT department of their clients. This is now on the change. A lot of IT service providers today really need to and are providing business value to their end clients. Such business value is provided only if there is business innovation. So it's not a service any more, it's a domain specific service and big data is doing a huge role there because big data is one area where Indian service providers can really provide that value to their end business and really provide very quick and disciplined value. UST and the Big Data Opportunity We are in the process of actually rolling out these solutions. In the sphere of big data, UST Global approaches the market as solution integrators and it's a very subtle step and an important one. If you look at the context of big data, it requires a vast knowledge in terms of processing the data, aggregating the data, advanced analytics, and deployment of the data. No single company always has that amount of scale or has the best analytical algorithm in the market. So we have partnered with organizations that have the best of breed in advanced analytics and other aspects. There is another shift happening today, i.e. moving from providing information services to information in itself. So rather than building an application that provides you information which will be information services building that application, you move towards actually providing the end information and that in terms of value is very highly quantifiable. For our customers, this is what we hope to provide. Challenges in Making Sense of Big Data One of the challenges and this is both for the UST and the end customers, is sometimes within the matrix that define the business value. There are some solutions such as personalized marketing which you distinctively know is going to have a huge impact but you have to go through a couple of integrative deployment of personalized marketing to really see what impact it is having in its top line and bottom line. Where several companies are trying to incorporate personalized marketing with all their available customers, we suggest them to start with a few number, do the personalized marketing, make a bench mark in the base line and then move on. So that is one of the most significant challenges which is in taking an integrative approach and impose to big bang approach. The second one is asking the right question. At UST we approach it with two questions, what if I quit, and then I wish I knew. To have really big data work for you, you have to ask the right questions, and that is what we consult to our clients to start with. From the past you can almost get very accurate data in specific geography even in the past five years. So what we did was take that weathered data and mapped it against the sales and transaction data of the retailers just to see what impact did that have on their stores sales for example. When it comes to challenge in deployment, the number one crisis in any clientele organization going down the big data line, it is the resources and the skill sets. Because big data is already spooning off new skill sets and most highly sort after one is data scientist, and he has to be creative enough as I said, not just ask the right questions by understanding the business but also have the scientific and mathematical background and statistical background to answer them, and crawl through the data to get the answer. At UST we are trying to build this scale as well not just for us but even for our clients in terms of data scientists who can crawl through and give the right answer and data savvy managers, who is the guy who can ask the right question. Strategies and Road Map At UST, we have segmented our 'big data' solutions into three houses — data and problem identification, data processing, and post processing analytics. We are approaching our clients to use these in developing the right capabilities and the right partners' ecosystem to deliver big data solutions to them.