Thanks For Your Feedback!

Five plus seven is? (answer as number)

Facebook Comments

Click to open/close fB Comments

Edge Analytics

The concept of “Edge Analytics” – i.e., the processing of analytics at the point or very close to the point where the data is being collected, which can exponentially increase the predictive analytics use cases for a casino. In short, edge analytics brings analytics to the data rather than vice-versa, which, understandably, can reduce cost as the data it analyzed close to where it is needed. This also reduces latency, which could be the difference between useful and useless analytics. As Bernard Marr (2016) argues in his article Will ‘Analytics on The Edge’ Be The Future Of Big Data?, “Rather than designing centralized systems where all the data is sent back to your data warehouse in a raw state, where it has to be cleaned and analyzed before being of any value, why not do everything at the ‘edge’ of the system?”

Marr (2016) uses the example of a massive scale CCTV security system that is capturing real-time video feeds from tens of thousands of cameras. “It’s likely that 99.9% of the footage captured by the cameras will be of no use for the job it’s supposed to be doing – e.g. detecting intruders. Hours and hours of still footage is likely to be captured for every second of useful video. So what’s the point of all of that data being streamed in real-time across your network, generating expense as well as possible compliance burdens?” The solution to this problem, Marr (2016) argues is for the images themselves to be analyzed within the cameras at the moment video is captured. Anything found to be out-of-the-ordinary will trigger alerts, while everything deemed unimportant would either discarded or marked as low priority, thereby freeing up centralized resources to work on data of actual value (Marr, 2016).

Besides the obvious use by a casino security team, for both patron and, potentially, perimeter security, edge analytics could be used to spot high rollers venturing onto a property, or uncovering problem gamblers, [EDIT]. “Large retailers could analyze point of sales data as it is captured, and enable cross selling or up-selling on-the-fly, while reducing bandwidth overheads of sending all sales data to a centralized analytics server in real time” (Marr, 2016). As today’s integrated resorts are also, in many cases, huge retail malls retail edge analytics could, potentially, become part of a package the casino company makes available to its retail clients.