Analytics for the Internet of Things (IoT)

Data validity

After finishing your completeness checks, it is important to check the validity of the data in the records that you do have. For each field in the measurements shelf, look for outliers well beyond any other data point. Also check for specific values that show up at a high frequency. The first could be either an error value or is serving as an indicator of an event other than a measurement. The second could be a default value that was intended to be overridden by the actual measurement value. There can be multiple explanations for unusual values; the goal is to identify the values and the approximate frequency of occurrence.

Looking at the Qgag values on a scale, it is apparent that there is a common outlier value on the negative ...