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Data science has become a key differentiator for many companies. We're here to help you figure out how to build your data science team.
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Posted by Scott Mutchler
Apache Spark is a game changer for big data analytics. In many ways, it will democratize analytics on big data. Spark will do this by making big data analytics accessible to a much larger group of data scientists (and analysts) via a simple programming API and familiar tools such as SQL, Python and R. Being open source, it will also allow many companies to embrace it with a smaller initial capital investment. Spark is also being embraced by IBM and other large analytic software providers as the engine that will drive their big data applications. The primary benefits of Spark are the ability to scale analytics to massive data sets and that Spark is a significantly easier to use platform (than Hadoop + Map Reduce + custom code) that will allow data scientists to be far more productive. Rapid development often results in a faster ROI.
Predictive maintenance (PM) programs, in asset heavy industries, can generate massive ROIs. These ROIs are delivered through the following benefits:
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