How India’s favorite TV show uses data to change the world
Satyamev Jayate, one of India’s highest-rated television shows, is using data as a means to effect meaningful change. The show’s producers are aggregating and analyzing the millions of messages they receive on controversial issues to do everything from planning future episodes to pushing for political change.
Data Science in India: meeting requirements, not just budgets
By Andrew Brust (Contributor at ZDNet)
It struck me that educational values and approaches in India might make Data Science skill sets there more abundant than in the U.S. and other developed countries. Perhaps Data Science will help India transcend the stigma/typecast of a tech talent center that is merely lower in cost.
India’s education culture is benefiting Data Science, and the country is producing Data Analytics professionals that compete not just on relative cost, but on absolute talent.
From the hub of the IT services sector, the shift is now toward making India an engine for knowledge-based services, with Data Analytics foremost among them.
Data decoded
Data, especially Big Data, is key to decision making and companies worldwide are starting to value this in their business. However, the mere volume of data is not the issue that organizations face today. It is the unstructured nature of the data and the challenge in extracting business value from it that is beyond the reach of traditional enterprise tools and business practices. According to a McKinsey study , the US alone faces a deficit of 140,000-190,000 data scientists against a projected demand of 440,000-490,000 by 2018. A shortage of the analytical and managerial talent necessary to make the most of Big Data is a significant and pressing challenge and one that companies need to address. Keeping this in mind, many Fortune 500 firms have already started to leverage India and its Data Science professionals to competitive advantage.
Destination, not detour
While many US firms were initially hesitant to work with an offshore provider, sourcing to India is no longer a taboo. But some are still skeptical about shifting work geographically for lower costs. For Data Science, India is not simply a cheaper alternative; it’s a go-to market for talent that can’t be found elsewhere.
Data Science and Big Data may mark a turning point for India and, most likely, other countries where mathematics education is heavily emphasized. Ultimately, markets that stress education in addition to technology innovation will be well- positioned. India’s proving that today.
How Big Data Startups Could Kill A $30 Billion Industry
When it comes to big data, “size doesn’t matter,” Ravi Mhatre, managing director of venture firm LightspeedVenture Partners just told Business Insider.
“It’s not just big data. It’s got to be fast data and it’s got to be meaningful data” he says.
There’s a new wave of start ups trying to make it easier to use big data systems. If they succeed, they will really hurt the multi-billion dollar market for business- intelligence software and threaten products like SAP’s Business Objects, IBMCognos and Oracle Hyperion.
“We’re talking an industry today that’s probably $20 [billion] to $30 billion that I think, overnight, is going to be replaced by a completely new set of platforms,” he predicts.
Future of data analytics is predictive, actionable
Move over, retrospective data analysis – the future is in real-time and predictive analytics, says a new market report from Frost & Sullivan. The trend is also toward web-based systems that aggregate disparate data across diverse care settings.
The more “holistic” approach to data mining includes clinical data from electronic health records combined with financial and administrative information to provide a more well-rounded view of the quality and efficiency of patient care and then using that information to make strategic decisions, according to a Frost & Sullivan announcement.
The firm predicts that the use of advanced health data analytics solutions in hospitals will grow significantly to 50 percent adoption in 2016 up from about 10 percent last year. That’s a 37.9 percent compound annual growth rate and an increase of 400 percent over the baseline.
“Hospitals will increasingly invest in advanced data analytics solutions to monitor end-to-end care delivery across a variety of settings,” Frost & Sullivan analyst Nancy Fabozzi said. “Due to growing competitive pressures, hospitals need to provide comprehensive reporting on performance and quality measures to a variety of stakeholders. Advanced analytics capabilities are absolutely critical for survival there is no way to avoid it.”
Customer Analytics: Social and Predictive Gains a Few Years Off
In a Forrester survey of 90 enterprises customer analytics practitioners, including insurers, social analytics is the most popular analytics program companies are looking to pilot in the next couple years.
The Forrester report, “The State of Customer Analytics 2012,” involved an extensive survey of 90 enterprise customer analytics practitioners in banking, finance, utilities and professional services. In it, the majority of customer analytics practitioners in the report noted mature use of reporting and BI (69 percent), descriptive analytics (81 percent) and predictive models (73 percent) for customer metrics. That level of adoption and use puts analytic prowess in marketing and sales above most other enterprise departments. Now, these departments plan to take their next forays into returns and develop their customer data resources, with a somewhat mixed bag of plans, says Srividya Sridharan, a customer intelligence professionals analyst at Forrester and an author on the report.
When asked about the top customer analytics program they planned to pilot in the next two years, “social analytics” led the way, though 30 percent of respondents pegged social analytics returns as a long-term goal. This is not be surprising in terms of social media data interest, but definitely “indicates that social data is still a largely unexplored data source” at the present, says Sridharan.
Sridharan says she expects businesses that have already made investments in better customer data management and measurements to take a serious look at predictive analytics as a next step. However, the Forrester expert cautioned that enterprises need to evaluate what returns they would expect from a predictive platform before diving in to an implementation, as well as take an inward look at the information at hand and how it would be managed moving forward.
“One of the prerequisites for predictive analytics is to have the right type of customer-level data available and accessible at the appropriate granularity in order to build predictive models. While firms can pilot or build models based on predictive analytics techniques, where they need to focus more is in putting these models and scores to work through marketing execution systems that actually manage customer interactions,” Sridharan says.
How CIOs Can Extract Value from Big Data
In a large retail chain, Big Data was used to tweak product pricing at the store level in real time, based on an evolving set of criteria ranging from point-of-sale data, to email-based promotions, to local advertising. Much like a doctor starting a diagnosis by taking temperature and blood pressure, then gradually refining each subsequent test, the reporting generated by Big Data rapidly evolved as the “diagnosis” progressed, with marketing driving the effort and embedded IT staff adjusting the technical side of the house in real time, based on the recommendations of cross-functional analytical experts. In short, marketing asked the question, the analysts determined what data were needed to answer it, and the IT people implemented the technical aspect.
Facebook Tackles (Really) Big Data With ‘Project Prism’
Facebook is staring down at larger avalanche of data, and there are new limitations that need fixing. This week, during a briefing with reporters at Facebook’s Menlo Park headquarters, Parikh revealed that the company has developed two new software platforms that will see Hadoop scale even further. And Facebook intends to open source them both.
The first is called Corona, and it lets you run myriad tasks across a vast collection of Hadoop servers without running the risk of crashing the entire cluster. But the second is more intriguing. It’s called Prism, and it’s a way of running a Hadoop cluster so large that it spans multiple data centers across the globe.
“It lets us move data around, wherever we want,” Parikh says. “Prineville, Oregon.Forest City, North Carolina or Sweden.”
