Big Data Analyzed, Visualized

Like many industries, insurers have been hard-pressed to effectively manage the large stores of data they accumulate, much less analyze it for additional gains. That may soon change with the prospects of a new in-memory business intelligence (BI) solution launched today by SAS. SAS Visual Analytics, part of the vendor’s analytics family, is being released with a visual interface that delivers analytics and insights to a broader class of users than before. According to an SAS spokesperson, while presently being touted by mobile telecom company Virgin Mobile USA, a Sprint prepaid company, at least one property/casualty insurer is among the product’s early adopters.

The product’s value proposition—applying analytics to massive amounts of data, being able to visually explore data at the speed of sight and the ability to share its insights with anyone anywhere—may send traditional insurance IT professionals scurrying to the corner. The product combines analytics, in-memory architecture, data exploration, Hadoop support and information-delivery options, including the iPad.

Indeed, the wave of the future may be here, Jim Kobielus, Forrester Research, has said.

Insurers need in-memory solutions that can make sense of their vast stores of data. Throughout the enterprise, from the overall call for organic growth, the data points now available via social media, the mandates for improved customer service, the need to sniff out false positives relative to claims fraud, and in capital management, where risk managers are held to instant evaluation of liquidity, insurers face pressure to make fact-based decisions faster. But to date, the hard and soft costs associated with such an initiative have held some insurers back.

Howard Mills, director and chief advisor of the Insurance Industry Group of Deloitte LLP encourages insurers to think about the value proposition of visual analytics. “The idea is to present the information in a way that is intuitively understood, with the relationships and the effect of relationship changes much easier to grasp than from a static table or spreadsheet. New and improved visualization tools include both open source and others from dedicated players and general technology companies, allowing for various entry or exploration costs,” he wrote in a recent INN blog.

“SAS Visual Analytics helps business users to visually explore data on their own,” said SAS CEO Jim Goodnight. “But it goes well beyond traditional query and reporting. Running on low-cost, industry-standard blade servers, its high-performance in-memory architecture delivers answers in seconds or minutes instead of hours or days.” Goodnight adds that the solution released today, which is based on the company’s LASR Analytic Server, leverages 35 years of SAS analytics research.

As a core component of SAS Visual Analytics, the SAS LASR Analytic Server uses Hadoop (embedded Hadoop Distributed File System) as local storage at the server for fault tolerance. SAS LASR Analytic Server has been tested on billions of rows of data and is scalable, bypassing the known column limitations of many relational database management systems (RDBMS), notes SAS.

The more data used in an analysis, the more accurate the results, making it a viable option when accuracy is critical in problem solving across big data environments, including both structured and unstructured data, says the company.

SAS Visual Analytics includes:

• SAS LASR Analytic Server - clients communicate with SAS LASR Analytic Server for calculations on the data resident in-memory, producing remarkably fast results.

• The Hub - a central location to launch the various elements of SAS Visual Analytics.

• Mobile - a tool for viewing reports, connecting to servers and downloading information on the go.

• Explorer - an ad hoc data discovery and visualization tool to explore and analyze data.

• Designer - used to create standard and custom reports and dashboards.

• Environment Administration - used by administrators to manage users, security and data.

Server components run on Red Hat or SUSE Linux, and the mobile client is available for the iPad from the iTunes App Store. Other mobile devices will be supported in the future.

While the high end is not limited, SAS LASR Analytic Server reference configurations begin with an eight-blade server with 96 processor cores, 768 gigabytes memory and 4.8 terabytes (TB) of disk storage. The upper end of the reference configurations is 96 blades with 1,152 cores, 9.2 TB memory and 57.6 TB of disk storage, enough disk space to store the entire Library of Congress six times.