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Josh Klahr

I've been working with data and analytics since 2000, including being the product manager for the first "Datamart in a Box" (Broadbase) and running product management for one of the largest Data and Analytics operations in the world (Yahoo!). I'm now applying these learnings at EMC Greenplum, where we are building the industry's first unified Big Data and Analytics Platform.

Posts by Josh Klahr

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This Big Data thing Is…Well…Big!

Early this year I made a big career move: after almost 7 years working at Yahoo! I joined Greenplum as our VP of Product Management.  The excitement of the new job has been exhilarating — new industries to understand, Big Data challenges to solve, and the fast moving pace of a “start-up-like” company.  I’ve always enjoyed learning new things — it was what I liked best about working in the central data team at Yahoo!.

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Agile Analytics Lifecycle

Agile development has been all the rage for a while now – extreme programming, scrum, user stories, epics, backlogs, etc. have become the lingua franca of any software development organization worth it’s salt.  And although notion of agile development hasn’t yet completely penetrated other parts of the enterprise, there is an increasing awareness of the benefits of agile development.

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Top Players by Points

As a data guy, I have always enjoyed learning about the power of statistics combined with the right metric(s) – together these two components are able to be used to drive effective decisions that lead to a desired outcome.  A great example of this – as I am sure many folks are already aware – is documented in Michael Lewis’“Moneyball”.  In a nutshell, Moneyball describes how Oakland A’s General Manager Billy Bean was able to use “The Right Metric” – in this case On-Base Percentage – combined with statistical analysis to effectively acquire players that led to overall team success.  This approach is nothing new in the world of sports or business, but it’s good to have this constant reminder of how creative thinking (the pursuit of the right metrics, the right attributes) and modeling (using the tools of Data Science) can lead to remarkable results.

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