I am looking for an advice.
We have a SQL Server database that records the various compositions of the daily raw feeds to upstream units for each of our plants. The data is therefore by definition time-series and indexed by plant, unit name and raw feed type with a value of volume/day.
Because these data items are related, there would be a natural fit with context items and fields.. They could also be ingested as individual tags with a unique naming convention by plant, unit, raw feed type.
Our primary objective is to troubleshoot and perform root cause analysis for issues observed on downstream units based on the various daily raw feed blends. This definitely involves time shifts and also value-based searches + event analytics.
Even though the data is naturally organized as event frames or context items, I am inclined to prefer ingesting this data as individual tags to enable diagnose/cross-correlations, event analyses and possibly fingerprint, unless there is something I am missing with the possible use of context items with these tools.