Add human knowledge and contextual information to Big Data to derive striking new insights

Modus Operandi lets you add human knowledge and contextual information to take analytics further and derive new insights that might otherwise be missed

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Big Data involves sifting through massive amounts of structured and unstructured data to find patterns and make connections that might otherwise be missed. Now Modus Operandi is taking Big Data to the next level through advanced data modeling that captures situational awareness to get even more insight from the available information.

For 30 years, Modus Operandi has provided sophisticated contextual pattern recognition for U.S. military and government agencies. Now the company is offering its Big Data analytics platform, MOVIA, to the commercial sector.

According to Eric Little, vice president and chief scientist at Modus Operandi, MOVIA is an unprecedented kind of software application. Not only does it ingest data from the typical sources of databases, devices and sensors, but it also incorporates situational context and human intelligence reports. Giving an example from military intelligence, Little says MOVIA can ingest information such as "I saw John Smith here and he was talking to Josh Jones over there." This information, in context with other data, could have implications for something like a potential terrorist attack or guerilla warfare operations.

Little gives an example of how this could help, say, a health insurance provider that has lots of legacy data. There's data from claims that detail who got what treatment from which provider. There is information about medical diagnoses and treatments, ICD-9-CM data (diagnosis codes), CBT (cognitive behavior therapy) codes, and laboratory data. There's information coming out of electronic health records, and information about clients, like what their socioeconomic status is, where these people are located geographically, the kinds of healthcare services they are using, what type of insurance they are buying, what their general health profiles and family medical histories are, and so on.

Now add current contextual information. For example, whether it is flu season, what strain of flu is prevalent, how effective the current flu vaccine is, what demographics are most susceptible to the flu, where major flu outbreaks are occurring, what healthcare professionals are actually observing.

Feeding this information, along with the other data, into the MOVIA platform and doing the analysis can help predict specifically which of the insurer's customers are most likely to be severely impacted by flu in the near future. To be proactive, the health insurer can directly contact its most vulnerable clients and urge them to get a flu shot, perhaps even arrange clinic appointments or schedule visiting nurses. For the insurer as well as the patient, an ounce of prevention is worth a pound of cure. The patient stays healthy while the insurer saves money by avoiding claims.

Modus Operandi normally provides some up-front services to get its customers started with the product. The services typically entail identifying areas of data that make sense to integrate, building ontologies and models that capture the appropriate data, and building the rule sets. Chief scientist Little says that a user can model the data according to human concepts, meaning the product is designed to work like people think as opposed to how a structured database forces people to work. "MOVIA captures and translates human knowledge and real-time analysis into embedded applications, and allows automated decision-making that thinks more like you rather than making you think like your days," says Little.

This type of application can appeal to a broad range of markets. Modus Operandi says it is already working with customers in cyber security, bioinformatics, pharmaceutical, financial, manufacturing and retail sectors. According to the vendor, the MOVIA analysis platform provides a tool that shrinks down many of the complex tasks of analyzing large amounts of Big Data that traditionally have required data scientists.

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