Continuing the discussion from How to properly do this join?:
Following up on the above discussion, after joining the two datasets together (Targets and Sales), the Sales dataset is not updating when I refresh it. I initially spotted this after realizing some numbers are off and came to find out that the sales from yesterday and the day before are gone.
I made this join on the 20th, last friday. It’s missing the sales that occured after this date, so no sales between 21st and 25th (today).
In the screenshot below you can see the structure of the join, with the Sales dataset (the one in the red box) being the one that I need to update. It updates just fine when taken by itself in an analysis, but once joined it’s stuck in the same way it was on the 20th.
My question is, how can I get the dataset to update once joined? Do I need to do something to get it to update? I have tried refreshing the joined dataset, see screenshot below, but this didn’t work.
Hi @SuciuAlex
I see that your targets is an xlsx file. The xlsx does not change once it has been uploaded in a dataset.
Have you checked to see if you have data for Jun 21st onwards in the file?
Regards,
Giri
Hi @Giridhar.Prabhu,
I am referring to the Sales dataset on the right, that’s the one that’s not updating.
The xlsx file has months, so I don’t see why it would get data from the 20th but would fail to get the same data from the 23rd.
It’s formatted like this:
| Agent |
Year |
Month |
Target |
| Rep 1 |
2025 |
1 |
1.000,00 |
| Rep 1 |
2025 |
2 |
1.000,00 |
| Rep 1 |
2025 |
3 |
1.000,00 |
| Rep 1 |
2025 |
4 |
1.000,00 |
| Rep 1 |
2025 |
5 |
1.000,00 |
| Rep 1 |
2025 |
6 |
1.000,00 |
| Rep 1 |
2025 |
7 |
1.000,00 |
| Rep 1 |
2025 |
8 |
1.000,00 |
| Rep 1 |
2025 |
9 |
1.000,00 |
| Rep 1 |
2025 |
10 |
1.000,00 |
| Rep 1 |
2025 |
11 |
1.000,00 |
| Rep 1 |
2025 |
12 |
1.000,00 |
| Rep 2 |
2025 |
1 |
1.270,00 |
| Rep 2 |
2025 |
2 |
1.270,00 |
| Rep 2 |
2025 |
3 |
1.270,00 |
| Rep 2 |
2025 |
4 |
1.270,00 |
| Rep 2 |
2025 |
5 |
1.270,00 |
| Rep 2 |
2025 |
6 |
1.270,00 |
| Rep 2 |
2025 |
7 |
1.270,00 |
| Rep 2 |
2025 |
8 |
1.270,00 |
| Rep 2 |
2025 |
9 |
1.270,00 |
| Rep 2 |
2025 |
10 |
1.270,00 |
| Rep 2 |
2025 |
11 |
1.270,00 |
| Rep 2 |
2025 |
12 |
1.270,00 |
Hi @SuciuAlex
From your earlier post this dataset is at the Month Granularity and the two tables are joined based on Agent, Year and Month.
So I would assume then that the Sales table that you are referring to has data updated as of 20th and may need to be refreshed to get updated MTD data in the source.
You also mentioned that when you reference the Sales table directly it reflects upto date data. Is it this same sales table or a different one?
Regards,
Giri
Hi Giri,
Yes, this is correct. They are joined based on Agent, Year and Month.
This is also what I think, it needs to be refreshed. The problem is that, when refreshing the JOINED dataset, even with the refreshes being successful (as you can see in the screenshot in the post), it still does not bring the up-to-date information. It still has the same information it had on the 20th.
It’s the same Sales table. The only difference is that, after I joined it to the Targets table, refreshing it brings no new data. If I use it by itself, this new data is there.
Hello @SuciuAlex
Are you still dealing with this issue or were you able to find a solution?
I’m curious if you make the Sales table the parent dataset in this instance if it will refresh properly. So when creating the join, start from your SPICE dataset rather than the xlsx file. I’m not sure this will make a difference but I think its worth troubleshooting.
Hi Duncan,
Yeah, I found out that I was accidentally not even using the joined dataset I mentioned in the post in my actual analysis, and I was actually the test version of this I created and forgot to delete… so once I actually used the correct dataset, it worked.
Thank you for your help!
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