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I interesting worked on a project as a data scientist with a client who worked in high precision manufacturing. Their signals (sensors) and actuators were stored in a historian which couldn't handle data 100ms samples even though the data was collected at a 10ms rate. One of the problems required us to look at the process that took just 85ms. The problem was the historian was showing signals up to 20ms it took a while to realise that it was extrapolating when you tried getting finer resolution. The company was using this historian for more than 20 years they had to commission another project to change the historian. So you're right, you don't know what you need until you need it.



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