Silicon Angle – Banks, retailers, Google, the NSA, they all lover their data. But one of the more intriguing use cases for Big Data involves the gambling industry, a sector that’s so reliant on number crunching and intelligent prediction that it’s been left with little choice to grab a hold of its masses of data and exploit it to the max.
The first adopters of Big Data in the betting game were, unsurprisingly, the bookies themselves. UK bookmaker Paddy Power‘s experience is one that mirrors that of many leading betting sites, when the rise of online gambling meant that it was accumulating hundreds of terabytes of data that it had little idea what to do with.
“We had a start-up culture. [In BI], we managed more than we thrived,” Conor McMenamin, Paddy Power’s business intelligence manager, explained to ComputerWeekly.
The problem with online gambling is that it’s a hugely dynamic business, with odds constantly evolving in real-time. This makes standard data warehousing techniques redundant, as bookies need to be able to access their data instantaneously. Paddy Power got around the problem by adopting QlikView’s business intelligence solution for live data based on Microsoft SQL Server and SQL Server Integration Services with Excel-based clients.
“It was about putting in place a scalable platform that we could develop on quickly, and not be constrained by legacy issues,” McMenamin adds.
Paddy Power’s self-service BI model meant that its decision makers had wider access to the company’s data in way that keeps its IT managers in control of governance and data structure, whilst affording managers more time to focus on their strategic goals.
Betting firms aren’t the only one’s using Big Data in the gambling sector. Some services are also looking at ways in which data can be delivered to the gamers themselves, providing insights that enticing them to stick around and, presumably, increase their chances of cashing out. This is the promise of poker stats firm SharkScope, which recently deployed the TokuDB’s performance engine to optimize its database performance.
