British Telecom had a problem: The company was suffering an ongoing series of security breaches — the physical, not cyber, kind. Thieves were stealing the company's underground copper cable.
Obviously, for a service provider like BT, the problem was not just about the cost of replacing the cable. It was also about customer relations. "It was damaging the brand," said Bryan Fite, BT's U.S. and Canada security & mobility portfolio manager, noting that every time there was a theft, customers lost service. A report in The Register said metal theft was costing taxpayers 700 million pounds per year.
This theft did not involve data. But it was data that solved the problem — Big Data analytics. Fite said BT had effective tools to investigate the crimes, but wasn't using them to full advantage. It had multiple sensor networks that could tell when people were on tracks or on cables, a fault system to tell when a cable was cut and closed-circuit TV monitors as well. "But all those were isolated, stand-alone," he said.
Using Big Data analytics, "allowed us to throw all that into an analytics engine. We did and they (law enforcement) busted a lot of the rings."
In one of those cases, two men were sentenced this past February to 16 months in jail after they admitted to stealing hundreds of meters of copper cabling from locations in Teddington and Sussex.
"When you overlay sensors, that's a good use of technology," Fite said.
Big Data analytics were also at play in the recent conviction of two Steubenville, Ohio high-school football players for raping a 16-year-old girl. Richard A. Oppel Jr., writing in the New York Times, noted that, "The verdict came after four days of testimony that was notable for how Ohio prosecutors and criminal forensics investigators analyzed hundreds of text messages from more than a dozen cellphones and created something like a real-time accounting of the events surrounding the incident and aftermath."
While hundreds of text messages do not amount to Big Data in terms of volume, the analytics do. Drawing connections among otherwise disparate data was not being done even a few years earlier.
Indeed, Big Data has revolutionized marketing and business operations, so it makes sense that it is also revolutionizing investigations, which are, after all, about collecting and analyzing information. Big Data analytics should make them faster, easier and more accurate, right?
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