Hi @Jille,
The approach that works well here is combining a Value-Based Search on the TM_hour time tag with Event Analytics Scatter Plot.
Step 1 — Set up the search
Open a Value-Based Search, set your context bar to the history window you want (-30d or -1y), then add TM_hour_Europe_Brussels (or the timezone variant for your site) with condition Constant and a minimum duration of 2 minutes. This produces one event per contiguous clock hour — 24 events per day, ~720 for 30 days, ~8,760 for a full year.
Step 2 — Add two calculations
- End value of
TM_hour_Europe_Brussels — gives the integer hour (0–23) at the close of each event. - Average of the process tag you want to profile or any other calculation available.
Step 3 — Open Event Analytics → Scatter Plot
Switch to the Scatter Plot tab and set:
- X-axis → End value (TM_hour_Europe_Brussels)
- Y-axis → Average [your process tag]
Each dot represents one hour-block from one day. The 24 vertical columns show the distribution of your tag at each clock hour — the typical day shape is immediately visible, and the spread of each column tells you where variability is highest.
This workflow is also described in the community here (steps 1–4 of the multivariate insights post map onto exactly this approach):
The TM_hour_* and TM_day_* family of time tags are also described in:
Kind regards
Frederik Vandael
