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It probably could be but not exactly as you want. Anyway, ask yourself what would this look like? What would your x-axis be? The granularity of the axis has to be a week, so how do you show a month? Relationship of a month & week is not 1:4 or anything like that. We also can’t put multiple x-axis in the chart, and that I’m happy about (in this case it could create more confusion).
We not use separate tiles that show week and then monthly numbers?
@Dawid Building off of this question, is it possible to do, without using merged looks to get the agent metric and the team metric (which the agent sits under) in the same timeframe on the same chart?
I’m trying to build agent performance dashboards and think it’s important to show the comparison with the team’s average performance to showcase whether or not the agent is under or over performing in their key metrics
Yes, I can see many use cases for such analysis. There’s an easy way and not so easy.
The easy would be to aggregate team numbers in your data model, provided that granularity stops at agent. However, if you have timeframe involved here, which I suppose you do, that idea may be to simplistic to allow for flexible on-the-fly aggregation.
The other approach would be to use these hacks in a Table Calculation:
I haven’t tried it myself though so can’t vouch for it being a good fit for your analysis.
Another way would be to create an NDT for teams and join it back to agent explore. It’s not easy either, as the time field comes into play (you may want to have this aggregated daily, weekly, monthly).
Window functions in Looker, or the inability of using them in any easy way, is one of the main pain points - we all feel it 🙂
Thanks for your quick response! It’s a shame that it isn’t easily built in functionality to Looker already to cater to these types of analysis
By the NDT option, could to explain more as it feels like it becomes inefficient to have all the calculations stored already in the table.
I have a situation where there is an agent, TL, area and dept level, so to have 4 different window functions pre calculated already doesn’t scale well.
I want to go a step further after this and use filters that if an agent’s email is selected, it identifies the average for their TL, if a TL is selected, it pulls the average for the area, etc all the way up to group function. This way there is only 1-2 dashboards to maintain which can be used by various user groups and view data on different levels.
Do you know if the above is easily possible, or is it better to build separate dashboards for each level? @Dawid
If you also have a time-related field in this table, it would probably be very tricky.You could create a daily aggregation table for an agent and also add the aggregation for your levels (area, group). Since these are discrete measures, you will still be able to sum them all up (aka. all days to get a monthly total)..
With averages, it gets trickier because you need to know the count of agents in that timeframe.
It’s hard to say for sure as it would require some planning and coding, but some parts could be possible. I can’t say to what extent though