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Big data will be big business in India

AP Photo / Gautam Singh
Data analytics represents a booming business for India—but first workers must be trained.
Published Last updated This article is more than 2 years old.

Just over a decade ago, as the world panicked over what would happen when 1999 turned into the year 2000, India threw down the gauntlet, proving it could write software and manage big tech projects with the best of them. Now India is ready to prove that it’s got the chops to tackle “big data.”

You’ve probably been hearing a lot about big data lately. In fact, you probably can’t get away from it. Literally. Your smart phone won’t let you, nor will your TV set top box or even your car. Everywhere we look (and even some places we don’t) we leave traces of information that Google, Facebook, and countless other companies can piece together to get a better idea of what we do, where we go, and what we like.

But big data is a pretty empty concept if you don’t know what to do with all of that information. Businesses like the search engines and social networks need help exploring the wealth of data they collect, to extract meaning from a deluge of numbers that will help them better understand market trends, their customers, and even their own operations.

India, more than any other country, has the resources and experience to make big data work. Sure, Eastern Europe and China might be emerging locations for analytics talent, but the world already knows about India’s prowess in delivering information technology services. The Year 2000 (Y2K) remediation opportunity was a great catalyst for the growth and establishing the credibility of the Indian IT services sector.  

Just like back then, there is no way the United States can tackle the business of data alone. A report last year by the McKinsey Global Institute, the research arm of the consulting firm, projected that US companies will need 440,000 to 490,000 data scientists and another 1.5 million data-literate managers by 2018. That’s great news for the economy. Unfortunately, the report also points out that the domestic talent pool to do this work will fall short by 140,000 to 190,000 professionals.

India is poised to step in and has made significant inroads in the data science field. By 2020, about 136 million Indians will join the global workforce. India is unique in its demographic dividend, while China and Eastern Europe face aging populations that limit the size of their workforce. Meanwhile, by 2025, one-quarter of the world’s workers will be Indians.

According to the Avendus Capital report, the market for global data analytics outsourcing stood at $500 million to $550 million in 2010. Service providers that predominantly use India as their delivery platform—such as my company, LatentView—captured $375 million, or nearly three-quarters, of that market. Unlike the growth rates of larger IT services and business process outsourcing (like call centers and medical transcription), the momentum in global data analytics outsourcing isn’t slowing. India’s competitive advantage in the data analytics field will continue—the country is expected to pull in nearly $1.2 billion in data analytics business by 2015.

To be sure, India needs to address gaps in its education systems that limit the employability of large numbers of graduates. India has to particularly develop employment-ready pools of people with better soft skills (such as communication, presentation, articulation, assertiveness). Further, India needs to develop talent beyond traditional quantitative disciplines such as STEM (science, technology, engineering, and mathematics) to areas such as behavioral sciences, visual communications, and business communication to fully address all the skills that analytics talent needs.

None of this comes cheap of course. That’s why India is grabbing a big chunk of investment money to help its data analytics businesses grow. Of the more than $2 billion that leading private-equity and venture-capital firms invested into big data analytics firms in 2011, an estimated 25% went to firms that have an India connection—more than any other region worldwide.

For workers to truly be ready for the big leagues of big data we need partnerships, especially with well-established tech companies and prominent universities. Such partnerships have already introduced a wide range of courses relating to statistics and data analytics. One example of this is the top-tier Indian Institute of Management-Lucknow, which is teaming up with the US-based Kelley School of Business at Indiana University to provide courses focused on data analytics. This is crucial to producing graduates with the skills needed to fill the growing demand for data analysis.

All of this sounds impressive at the high level, but there’s more to India’s story. Data analysis firms there understand that you can’t rely on an analyst based solely on his or her educational background. Good analysts need to know what they’re looking for in all of that data. Here’s how we do that at LatentView. We hire people with quantitative knowledge and engineering degrees and then train them for 12 to 18 months so they know how a client’s business works. If you want useful information out of your data, the person analyzing it needs to be able to see the big picture. To derive insights, one needs an optimal combination of business knowledge, data analysis and quantitative skills. The data analytics firms are able to engage with marketing leaders and address their business questions more ably than traditional IT services firms.

Another area of data analysis I should address is privacy and propriety. It’s the elephant in the room—everyone wants to collect data from mobile phones, tablets and video game systems so they can sell people more “stuff.” But it takes a solid game plan to make sure this data isn’t stolen, lost or misused.

Good data analyst firms will cross-pollinate ideas from the various business sectors they manage. If they can come up with a successful plan for one client, that approach will likely work for others as well. But this doesn’t mean client data is somehow exposed or less secure. For example, LatentView doesn’t have personal identifying information, so this limits our potential for exposure. And our clients are protected by confidentiality agreements, firewalls, service level agreements (SLAs) and solid infrastructure to maintain data security and privacy.

Of course, ultimately, it’s up to Indian firms to walk the walk when it comes to big data. Indian companies have the opportunity and the potential to significantly address the talent gap in analytics. By navigating the challenges by developing its own talent pool, the country is well on its way to realizing this potential and redefine its tech sector.

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