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Dataveillance: Detecting the Danger ‘Lost’ in Data

10 July 2017

Sort, Combine & AnalyzeOperators working in today’s data-rich environments cannot access the level of situational awareness they need to operate securely and efficiently using visual information alone. The widespread adoption of IP solutions and increased digitization of security, safety, and operational systems means no single system can give businesses the comprehensive view needed to identify and efficiently neutralize risk.

Cameras, alarms, point of sale, process management, access control, and any number of other third-party systems all generate data critical to identifying and dealing with threats. Data integration is key, but the mountain of information this generates is often too vast to understand in a meaningful way. It’s a challenging dilemma.

What’s needed is a way to combine and mine data from visual surveillance, alarm and transactional systems, to identify events and risk indicators that would otherwise be virtually impossible to detect. Dataveillance does exactly this.

In this special three-part series, we look at Dataveillance in detail and speak to a number of Synectics experts about the origins of this particular management tool, its evolution and how we can expect to see it deployed in the future. Here we talk to Martyn Rowe, Head of Client Delivery about what exactly Dataveillance is and how it came to be.

How would you define ‘Dataveillance’?

Dataveillance is a way to cut through irrelevant ‘noise’ in order to quickly see the information that truly matters. It’s more than data integration - it’s a customizable tool for automated data interrogation.

Modern surveillance command and control platforms allow data from multiple video, alarm, process and transactional systems to be accessed, monitored and managed in a single unified environment. While this makes life much simpler, you still need to be able to sift through data to determine what really matters. For large complex sites or organizations with multiple locations, this can be a daunting and resource-draining task.

With Dataveillance the ‘sifting’ is automated. Information from integrated systems is pushed to the surveillance network from integrated systems, where it is sorted and organized into a structured, common database which can then be interrogated and analyzed in real time with user-defined rules.

In the very first application of Dataveillance within our Synergy solution, the rule in question was an algorithm to detect gaming fraud.

How did this first use of Dataveillance come about?

How many of our solutions come about - through listening to a customer.

Darrin Hoke, the Director of Surveillance at a casino we had worked with for many years, had uncovered a scam where comps were being issued for high-value play that didn’t actually occur. By looking at the initial chips purchased and the maximum players could have bet within an hour’s play, Darrin discovered that comps awarded couldn’t possibly be warranted. Play was being inflated to secure comps that weren’t deserved.

On retrospective investigation, he found that this one specific type of ‘cheat’ had cost the house almost $500,000 in the space of a year.

For Darrin, this investigation was a very manual process that involved trawling through spreadsheets, footage, and player data. It was a problem that surveillance alone could never reveal. It also wasn’t a scam the casino’s player tracking system could ever detect as there was no way for Darrin to apply and alarm the algorithm he’d developed.


Bonus Video: The Origins of Dataveillance

Watch Darrin and others dicsuss Dataveillance way back at G2E 2009, including the practical application of data analytics and its potential beyond traditional surveillance applications.

Watch Now >>


So you developed a way to incorporate the algorithm within your surveillance solution?

Yes. What we quickly realized, however, was that the power and potential of Dataveillance wasn’t in applying a specific algorithm, it was in giving casino operators the means to apply any algorithm (rule) they wanted, based on their own expertise, experience, and business needs.

With this capability, casinos could (in real time) quickly see, for example, when point of sale refunds are issued when nobody is line; when frequent pay outs mirror specific dealer shifts; when regular players start placing unusually high bets. By applying rules based on time frames, financial values, averages, or any combination of user-dictated criteria, casinos would have the freedom to fine-tune their entire surveillance solution to better detect threat.

Also, as scams, frauds and security risks are constantly changing, it stands to reason that threat detection tools should be equally adaptable. By conceiving Dataveillance as a customizable data analysis engine within our Synergy command and control platform, rather than a prescriptive tool, we created a solution that could help casinos stay a step ahead.

If it is non-prescriptive, does that mean any sector can use Dataveillance?

Absolutely, and that’s what we’ve found. Although the solution’s genesis was gaming, its relevance is universal to complex environments where security is mission critical.

With increased digitization of consumer and industrial settings, the need to identify ‘danger hidden in data’ is ever present and ever growing. Synergy 3’s Dataveillance engine offers a solution by making data both meaningful and manageable.

The next step for us, of course, was to make the information obtained easily ‘actionable’ as part of the same solution, and that’s where developments such as workflows have really taken things to the next level.


Thank you, Martyn. In the next edition of our Dataveillance Interview Room series, we talk to Neil Waudby, Software Development Director about how Dataveillance has evolved and has driven key features, including workflows, within Synergy 3.