Why it is important to recognize bad engineering data before using it for durability and performance analysis
Collecting good time series data is not a trivial task. This presentation will shed some light on causes and examples of bad data, and what separates good data from bad data. We will explain ways to recognize bad data, and suggest best testing and analysis practices to ensure the best possible engineering decisions are being made.
Good Data Gone Bad (pdf)