What factor impacts the accuracy of the PercentGood column in AnalogSummaryHistory?

The accuracy of the PercentGood column in AnalogSummaryHistory is influenced by several interrelated factors, making the option that includes all of them the most accurate.

Firstly, the frequency of data updates plays a critical role because if data is updated infrequently, it can lead to gaps or missed data points during the analysis period. This can skew the percentage of good data, as the history might not reflect the true operational behavior of the system.

Secondly, the quality of source tag data is fundamental for calculating PercentGood accurately. If the source tags are providing erroneous, incomplete, or unreliable data, then even a high frequency of updates will not create an accurate representation of the actual process conditions. Thus, poor-quality data directly impacts the perceived validity of any summarized data.

Thirdly, the time range selected for summary also affects the PercentGood calculation. A longer time range may incorporate more variability and potentially include periods of poor data quality, while a shorter time range may yield an artificially inflated PercentGood if it captures mostly good data points without adequately reflecting the overall system performance.

In summary, each factor contributes uniquely to the calculation of PercentGood in AnalogSummaryHistory, shaping its overall accuracy. Therefore, considering all these aspects together provides the best understanding of how this metric is