Using Big Data Analytics as a 'Competitive Hammer'

Barry Ralston, AVP for data management at Infinity Insurance Companies, is a big believer in the power of big data to help gain an edge in the marketplace. Recently, Ralston sat down with Dana Gardner, principle analyst at Interarbor Solutions, to detail his approach to making big data a competitive tool within the insurance sector.

Infinity, a billion-dollar property/casualty company headquartered in Birmingham, Ala., has taken a leadership role in terms of data analytics, Ralston explains. The company fully grasps how and why data is a strategic weapon.

The latest development in this strategy is deploying a column-store database environment, which provides the company more flexibility and more expansiveness in analyzing its data, Ralston explains. Column-store databases, part of a new breed of data environments arising to meet the challenges of managing big and unstructured data, break down records into columns, thus spanning field categories as opposed to traditional relational databases, which store data as rows. This drastically speeds up data compression and sorting.

The ability to process and analyze data at a faster rate than previously possible in its traditional data warehouse environment gives Infinity a leg up in the marketplace, Ralston explains. “Insurance is an interesting business in that, as my product and pricing people look for the next great indicator of risk, we essentially get to ride a wave of that competitive advantage for as long a period of time as it takes us to report that new rate to a state,” he says.

As a result, the insurer's column-store data environment — in this case HP's Vertica — along with Hadoop serves “as a competitive hammer,” Ralston says. The company can “do things that competitors aren’t able to do.”

The key is to develop an architecture that is able to move data quickly to wherever and by whomever needs it. “The great question is what ends up being the business value,” he says. Business analysts, he continues, “don’t necessarily have to be data scientists” to benefit from this type of architecture.

Most existing data environments and data warehouses were not designed or built to cost-effectively or smoothly handle large quantities of both structured and unstructured data. Insurers need to explore and experiment with new types of architectural approaches to the challenge — this includes column-store databases, as well as other types of NoSQL, NewSQL databases.

Joe McKendrick is an author, consultant, blogger and frequent INN contributor specializing in information technology.

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