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How to Identify Data Patterns (Bad/Stale/Flat-lined) over a time range using Datalink functions

Question asked by R.Shende on Oct 1, 2019



I am trying to develop Datalink queries to execute over a range of time and data events to identify various patterns such as - Bad Data, Data Freeze (Stale Data), Data Flatline and so on.


Could you please guide on how should I design the expression to identify the following data patterns in the given data set and which may span over any portion of a given time range (i.e. not necessary that these patterns are currently existing for a given tag - they may have occurred in the past during the given time range)  : 


1. Bad Data

2. Data Freeze (Stale Data)

3. Data Flat Lining (Same value coming in)

4. Check the time range when the value of the tag was not as expected (i.e. outside the range (Zero+Span), not equal to a specific/desired value etc.)


Thanks and Regards,

Rohit Shende