Gamification is spreading its wings, more than ever–to different domains and verticals. It can turn any boring thing into an interactive and engaging stuff, such as corporate training. What makes it more interesting; rather useful is the use of Big Data in gaming that helps companies a great deal when it comes to understanding their players. But scaling big data “cheat” detection for real world problems of fraud may have similarities.

Online games frequently face the problem of cheating, that’s why gaming companies leverage Big Data to develop anti-cheat solutions. A prominent example is of Valve Corporation’s game platform, Steam, which developed an anti-cheat solution in 2006 after it detected 10,000 cheating attempts in a single week. As of 2012, it had terminated more than 1.5 million accounts within the 60 games running on Steam.

Most gaming companies these days have adopted the free-to-play business model and rely on in-game purchases and advertising. Since the basic game is free, currency plays a key role in the company’s ability to generate revenue. The problem for gaming companies arise when savvy social game players figure out a hack to advance without purchasing currency leading to frustration of honest players and losing of company revenue.

So here, Big Data comes into play. Gamers generate obscene amount of unstructured data, which can be put into work to gain actionable insights that identify and stop fraudulent game activities in real time. Same data can be manipulated to segregate cheaters from honest players, and then use analytics to eliminate fake accounts. Same data can also help identify vulnerabilities and fix them before exploitation.

So, the point is that gamification approach can be used by other verticals to identify potential pitfalls and solutions, such as for consumer and enterprise products. The elements of gamification can be used anywhere ranging from corporate training modules to calendars tracking fitness goals. Again, unstructured data can be used to limit fraudulent activities like identity theft, rogue servers, etc.

Big Data and gaming industry share a long term relationship, mostly symbiotic. The video game industry has grown from 200M active users to 1.5B players worldwide–each one producing a vast virtual footprint every time they go onto one of the games that they play. If that isn’t the definitive “big data” then nothing in this industry is. In fact, in a speech at Stata conference 2013, EA CTO Rajat Taneja spoke to audiences about how Big Data has inspired EA to upgrade their game.

Later last year, gaming giant King.com hooked up with Cloudera Hadoop to understand its players, who plays its games, how they play games, and when players are most likely to spend money on virtual items. It’s because Hadoop provides not just a processing system for historical data; but also the ability to watch current and real-time activity by users to help mold their experience and change user interaction on the fly to better adapt to them.