With the introduction of analytics tools, companies have started making decisions that bring definite and immediate business value. Analytics tools are being used to identify trends and patterns, and at the same time, to gather pertinent information from the mountains of data that is available. That analytics is being widely used in the telecom, retail and healthcare sectors, is well-known. Here are some offbeat domains where analytics is driving innovation.
Image courtesy: https://mrunal.org/2012/09/polity-natgrid.html
1. National Security – NATGRID: The National Intelligence Grid is the Indian government’s ambitious counter terrorism program. What is of paramount importance to intelligence agencies is the ability to track real-time information about suspects. The government, aware of the enormous potential of the data at hand, intends to use state of the art technology for data mining and fraud detection. Intelligence units of the government already have access to huge volumes of data. The challenge lies in being able to link suspicious or illegal activity – either physical or on the internet – with financial, telecom and other records.
2. Energy – Shale Oil Exploration and Production: You might have never heard of shale oil, a lesser-known, unconventional kerogen oil, which has made the United States an energy superpower. What is controversial about shale oil exploration is the fact that its horizontal drilling and hydraulic fracturing processes may also contaminate groundwater and cause earthquakes. And analytics will be the path oil and gas companies will tread, to make this alternate energy source safer and more efficient. Combine the findings of data scientists with those of geoscientists, and these companies will be landed with a wealth of complex data that will help them predict where to drill. Using predictive analytics, they will be able to integrate audio, video, textual and numeric data to drill for oil without jeopardizing the environment.
3. Music – Lady Gaga “Littlemonsters” and Shazam’s hotlist: It is no longer just the reviews and numbers that artists, music labels and agents go by. Popularity these days, can be gauged from monitoring social networking websites – Facebook, Twitter and Youtube, to name a few. One of the first artists to cash in on this data mining opportunity was Lady Gaga. Her agent integrated the data from various social sites and ticket sales to create a database of fans, whom they could successfully direct to littlemonsters.com, Lady Gaga’s own social fan network.
The use of analytics in the music industry goes beyond that. For example, Shazam, a popular song-find app, is using predictive analytics to create a list of artists to watch for in the next year. Shazam uses data which is a combination of critical acclaim and the number of listeners who have used the application to find a song, to arrive at a list of popular artists.
4. Sports – The Babolat Play: For an athlete, the interval of a millisecond could be the difference between winning and tailing behind. If you can track your morning walk with an app, there is of course a lot more data out there that is captured by sophisticated gadgets used to monitor athletic performance. Babolat Play is a high-tech racket that has revolutionized and made “connective” the world of tennis. This racket stores and analyzes every shot and provides a bird’s eye view of a player’s performance across games, including highlighting areas that need improvement, and areas that have been worked upon. Anxious traditionalists worry that coaches may go out of business, but this super-smart racket can surely complement a coach in improving a player’s performance – be it a beginner or a pro!
5. The UID Challenge – Analytics in Aadhaar: India’s population of 1.2 billion, all need to have an Aadhaar UID. While fierce debates rage on the utility of the Aadhaar, and whether or not the project should even be continued, what is noteworthy is that the UID project is a big data challenge. At the moment, almost 1 million UID cards are being issued everyday. The volumes of data that are generated are unimaginable. The fact that all of the data entering the system has to be compared to and matched against pre-existing data, makes it an even more daunting challenging. The Aadhaar UID uses analytics platforms and tools to integrate all the data, and ambitiously aspires to link bank accounts and various other services to this primary database.