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Pepperdata: Bringing DevOps Practices to the Big Data Worldby@ChrisChinchilla
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Pepperdata: Bringing DevOps Practices to the Big Data World

by Chris ChinchillaSeptember 6th, 2017
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Big data analysis generally involves piping large data sets into processing systems such as Apache Spark and Hadoop, walking away for a very long coffee, and returning later to a hopefully successful result. The DevOps and continuous build ecosystem have long employed linters, code analyzers, and application profilers to discern potential trouble and optimization points in code, and Pepperdata wants to bring that practice to the big data world.

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Big data analysis generally involves piping large data sets into processing systems such as Apache Spark and Hadoop, walking away for a very long coffee, and returning later to a hopefully successful result. The DevOps and continuous build ecosystem have long employed linters, code analyzers, and application profilers to discern potential trouble and optimization points in code, and Pepperdata wants to bring that practice to the big data world.

I spoke with CEO Ash Munshi, formerly CTO of Yahoo! and consultant to other data heavy tech companies, about what the company offers and how their customers save hours from running inefficient processing jobs.

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