Examples of Big Data Success: Making the Data Work to Solve the Big Problems

Sue Marquette Poremba

The number of Fortune 500 companies successfully using Big Data analytics as a way to improve business intelligence and efficiency is not very high. According to a Forbes article, it’s anticipated that the number could be as low as 15 percent. Among SMBs, that percentage is likely even lower.

One of the reasons so few are using Big Data is due to the lack of skilled professionals available to analyze the massive amounts of information being generated. Companies still don’t understand how to best leverage the collected data.

However, Big Data can be a real asset when properly utilized. It can customize customer offerings based on past purchases, it can anticipate supply and demand, and it can anticipate potential problem points and generate solutions. In short, Big Data can be a game changer for a business, as it was for these companies.

Big Data Example: URX’s Big Data Analytics Success with Mobile

URX is a San Francisco-based company that uses mobile deep linking technology to link content across devices. Its technology platform helps anticipate what mobile users want to do next and enables users to easily take action inside apps. A critical component of this technology is the ability to dynamically understand user intent based on the context of the page.

“URX analyzes text and metadata on the page and uses our knowledge graph to gain an understanding of what a user is interested in,” Delroy Cameron, data scientist, explained. “Given the sheer number of topics a user could be reading about and the actions a user could be interested in as a result, this becomes a tremendously complex and ever-evolving Big Data problem.”

Cameron pointed out that by using knowledge graphs and machine learning, the company could make sense of the people, places and things that are mentioned in order to recommend related actions. “We are continually ingesting data to train our machine learning models and improve our knowledge graph. Wikipedia is an incredibly valuable dataset for this task because it is a rich source of semantic information and is often considered a vast and comprehensive knowledge base. It’s also a heterogeneous data set with lots of diversity - information on people, sports, politics, companies and many things in between.”

URX believes that Big Data is at the epicenter of building cohesive mobile experiences, and its dynamic, real-time technology wouldn’t be possible without the ability to make sense of extremely diverse contexts and to recommend relevant actions. Big Data powers the very core of the company’s ability to deliver context-driven mobile experiences.

Big Data Example: GED Testing Service’s Big Data Implementation Success with Self-Service

GED Testing Service produced an annual paper report with data sliced by different dimensions—demographics and geography, among other areas. The paper was released in May the following year, which was pretty late in the year to make the best impact.

“We knew we wanted to move to an ad hoc platform that made it easy to see information, at-a-glance,” said Sarita Parikh Director, technology and operations at GED Testing Service. “It was important to give our customers a tool that had a lot of information, but was easy to use and easy to consume.”

So the company decided to turn to Big Data to build one model that's flexible enough for all customers. The GoodData platform that the company decided to use gives customers an easy-to-use, easy-to-consume view into large and complex data, anytime and anyplace, without heavy training.

Not that it has been without challenges. According to Parikh, internal buy-in to outsourcing data was the biggest trial. “After that, we had a lot of focused analysis, work, and customer advisory groups--it was complex, but it was aligned to our expectations.”

Security and privacy were important components that GED Testing Service had to consider before the company turned to Big Data. “At the time that we built our GoodData solution, our organization had not used any cloud-hosted platforms--everything was hosted in-house, with the sense that we would be the best stewards for the data,” Parikh explained. “We conducted a full analysis with our Chief Security Officer and GoodData's security platform knocked our socks off. We did ask GoodData to build encryption-at-rest, which is a core requirement for all of our systems containing private data. GoodData supported our request and has since expanded the use of encryption-at-rest to most of their clients.”

Overall, clients have been happy with the success of the Big Data solution. “The self-service model has been fantastic for our customers,” said Parikh. “They have on-demand access to slice/dice their data in thousands of different ways. We've had overwhelmingly positive response to our new data tool.”

Big Data Example: Chinese Community Health Care Association’s Big Data Success in Health Care

The Chinese Community Health Care Association (CCHCA) needed to close a communication gap between health providers and Medicare in an efficient manner.

“Medicare has asked us to communicate to them exactly how sick a population is. That way they can assign funds to appropriately meet care needs based on the severity or complexity of the patient’s health profile,” explained Donald Brandenburg, director of health information technology. “The problem lies in that the communication from the provider to Medicare is not done through written documentation, the technique that our health education system almost exclusively trains providers on – instead it’s done through an extremely complex coding system.”

CCHCA decided to turn to Apixio’s HCC Profiler to solve the problem, making what was a cumbersome, inefficient and costly process into something much more reliable, intelligent and efficient.

Big Data on its own isn’t a solution to anything, Brandenburg pointed out. It has to be properly utilized and analyzed to make it effective. For CCHCA, Big Data was able to be part of the solution because the company understood it didn’t have the skilled staff in-house and looked for a third-party company that did have the know-how.

“I think we can all agree that health care is an incredibly, incredibly complex system – a system where in order to make a good decision, you need to be well informed,” said Brandenburg. “At CCHCA, we don’t want to make good decisions, we want to make great decisions. That directive requires a lot of data, and even more importantly, a responsibility to refine, shape, mold and present that information back to our patients and their care team in a way they can understand and take meaningful action on.”

Having the right Big Data solution in place makes that happen.

Sue Marquette Poremba has been writing about network security since 2008. In addition to her coverage of security issues for IT Business Edge, her security articles have been published at various sites such as Forbes, Midsize Insider and Tom's Guide. You can reach Sue via Twitter: @sueporemba

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