The driving concept behind edge analytics is the fact that data loses its value as it ages. 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—exponentially increases one’s ability to use predictive analytics where it can be best utilized, at the source.

As Patrick McGarry explains in his article Why Edge Computing is Here to Stay, Edge analytics is easier to implement than ever before because in the field micro data centers use a fraction of the space, power and cost of a traditional analytics infrastructure, and they can provide massive performance gains. These systems use “hybrid computing technology, seamlessly integrating diverse computing technologies, whether they are x86, GPU or FPGA technologies, or any combination thereof. They are extremely compact in space and require very little power, yet still provide performance that is several orders of magnitude more than what today’s traditional systems can provide. “It’s a win/win situation for all involved; insights come faster than ever before, operational expenses are lower, [sic] power and administration needed to run the systems,” McGarry ads in his book.

Although building an edge analytics platform does require a shift in corporate thinking, the ROI benefits should far outweigh the costs. “The cost savings by scaling back central data analytics infrastructures to handle non-time sensitive analysis while installing cost-efficient platforms purpose-built for edge analytics can have a real impact on an organization’s budget,” McGarry notes. The value of near-instant analysis and insight cannot be underestimated in a business so dependent on customer excellence like the casino business. Avoiding latency and eliminating the time and costs associated with transporting the data to and from the edge is a major step toward achieving that goal.

For casinos, IoT sensors can help spot patrons arriving on property, or track employees, suppliers, and supplies throughout the supply chain, as well as help save energy and water usage. Edge analytics can help analyze retail customer behavior, as well as spot upcoming equipment malfunction. Other areas where it can help include compliance analysis and mobile data thinning, i.e., the culling of mobile data noise from social media or direct mobile streams. Personally, I believe edge analytics could be one of the top technologies that can give a casino company or an IR a competitive advantage over its rivals and I will provide more detail on how this technology can be implemented within a casino environment throughout the rest of this book.

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