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Analyze This: Big Data is insurance against losing a competitive edge

Nadhan on ‎08-02-2013 10:33 AM

“Data is key to what we do,” says Barry Ralston, Assistant VP of Data Management at Infinity Insurance in his interview with Dana Gardner.  Infinity, a billion-dollar property and casualty company, works with large volumes of data about customers, policies, payments, and etc. To retain a competitive edge in their industry sector, enterprises must proactively apply complex analytical techniques on data that matters. And they must do this quickly. This will protect them against unforeseen market downturns, such as consumers insuring themselves against unexpected calamities. So, where can enterprises get this insurance (of sorts) against the possibility of losing their competitive edge? Ralston's detailed explanation of Infinity’s solution suggests that the answer might be staring at us in the face — Hello Big Data!

Home inside Big Data.png

Let’s see how.


Ralston characterizes Big Data as a strategic weapon for Infinity.


This comes across very clearly as I read (and listen) to his interview. Here are the key points that surfaced along with some of my own thoughts.


1. Analyze data that matters. Ralston explains that the traditional concept retrieving whole rows of data elements is no longer an effective approach when complex analytics needs to be performed on a few columns representing the data that matters. When customers purchase policies, Infinity might be more interested in the top ten policies that are in demand rather than other details. Therefore, it makes more sense to retrieve, sort and analyze only the data elements that matter.


2. As you store, so you retrieve. Warehouse management is a well-honed science now, where pallets and items are placed in a manner that they can be easily accessed and retrieved. The frequency of access usually drives where and how it is stored. The storage architecture significantly impacts the ease of retrieval. Infinity’s solution follows this simple yet powerful principle, using column-based storage.


3. Improve performance at the origin. Time is vital when it comes to process data into information. Every nanosecond counts. Performance is a key architectural tenet that must be applied at the source of the data element. This will obviate the need for downstream reactive measures like in-memory databases and additional hardware.


4. Time-to-decision matters. Are we there yet when navigating the Big Data traffic jam? As Jaap Suermondt, Director of the HP’s Analytics Lab explains, Big Data needs to be available at decision time. Tools exist today that can process data to deliver information at decision time.


5. Get ahead of the game. “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 that wave of competitive edge for as long a period of time as it takes for us to report that new rate to a state,” says Ralston. Predictive analytics are vital to look ahead at what is coming to retain the competitive edge.


So, what is at the heart of this solution? Vertica Analytics Platform.


Wondering what the letters V E R T I C A stands for? Here is what I think.


Want to know more about this tool? HP's Big Conference for your Big Data.


Want to connect with me? Twitter, Facebook, Linkedin and Journey Blog.






Vertica Conference 2013.jpg

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