Meter data validating editing estimation

At the same time, Mc Kinsey found serious capability gaps that could limit an enterprise’s Io T potential.

However, the sheer scale of data being produced by tens of thousands of sensors on individual machines is outpacing the capabilities of most industrial companies to keep up.It is an approach that can be used as a model for other industries as well when looking to ensure data quality from high volume, high velocity sensor data streams.Today, business processes and operations are increasingly dependent on data from sensors, but the traditional approach of periodic sampling for inspecting data quality are no longer sufficient.This may be either in root-cause analysis to identify, say, large fluctuations in measurements from defined parameters that suggest component failure or in unexplained deviations from normal patterns that may signify environmental issues or perhaps a more insidious cyber threat that complementary analytics may investigate further.The VEE process is therefore applied to incoming data so that the data can be certified and used in analytics.

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