Cloudera customers: doing the impossible

Den Howlett Profile picture for user gonzodaddy March 3, 2014
Charles Zedlewski VP products at Cloudera offers four vignette case examples of how Hadoop systems are opening up new business opportunities. There's a lot to get excited about.

Last week I sat down with Charles Zedlewski, who runs product for Cloudera and spends a considerable amount of time talking to customers about the problems they are trying to solve. I've known Charles a number of years - he's a super smart, amiable and articulate person.

Cloudera is a database management business with a heavy emphasis on Hadoop and non-transactional systems, typically solutions requiring analysis of very large and diffuse datasets - the so-called 'big data' scenario.

Much is made of 'big data's' ability to provide the information that allows businesses to solve previously intractable problems and pose questions that earlier systems cannot handle. In the above video, I was keen to get Zedlewski talking to the specifics. Here's what he had to say:

For a lot of people, the fractional cost of running queries using Cloudera's Hadoop based systems is a 'door opener.' Here are are four vignette examples of the kinds of thing that Cloudera is enabling.

Cyber Security - A number of customers are handling hundreds of billions of IT events where they're looking for patterns that might represent a threat as compared to 'normal' behaviors.

Monsanto - developing new business models: Monsanto is taking geo-spatial and other data to figure out the seed sowing patterns that will deliver uplifted  yields for their customers. Early results are encouraging. That data is being sold as an additional service to farmers.

Commodity and retail trading: Skybox uses satellite images to tell traders how busy specific ports are for different types of commodity. It can also tell retailers how busy their shopping areas are by counting the numbers of vehicle in their own and competitors' parking lots.

Credit card: A large bank is taking both marketing and risk data to make the combined data part of a continuous analytic process. This optimizes marketing efforts while minimizing risk.

It is interesting that in  each of these cases, there are few pre-existing intelligence models that can be leveraged. Instead, customers are building their own models to solve problems that are specific to their circumstances and business models. This is a large step change in the way business moves forward.

Expect to see more of these stories...

Featured image credit: © Mark Carrel -

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