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4 Steps to Data Readiness for Industrial Analytics

I recently attended a workshop in St. Louis—Big Data, Predictive Analytics and the Industrial Internet of Things—sponsored by our partner OSIsoft, Rockwell Automation and Anheuser-Busch (the makers of Budweiser beer for the uninitiated).  The event focused on how industrial companies can deploy new technologies like cloud, machine learning and mobile to turn raw data into analytical information that improve businesses outcomes.  

The presentations were informative, but mostly missing from the discussion was a deeper exploration of how poor data quality makes effective industrial analytics hard to achieve, especially at an enterprise scale.

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