Forum Discussion
Visuals show incorrect data until I re-publish the dataset
Community SupportHi ChristianW ,
To help isolate the root cause, I would recommend checking the following:
Auto Date/Time or hidden date tables
If you're using the week as a string (e.g., 2026cw13), verify there isn’t any implicit date table or relationship causing unintended grouping behavior.
Column data types & sorting behavior
Ensure the week column is consistently treated as text (or properly modeled with a numeric sort column).
Mis-sorting can sometimes lead to aggregation overlap between adjacent periods.
Duplicate keys / granularity issues
Since underlying data exports are correct, validate whether there are duplicate combinations at the model level (e.g., Type + Week) that could be getting re-aggregated incorrectly in visuals.
Measure logic vs implicit aggregation
If visuals rely on implicit SUM instead of explicit measures, try recreating them using a DAX measure to rule out aggregation inconsistencies.
Service-side caching artifacts
Even with query caching disabled, there can be residual cache behavior.
As a test, try:
Clearing dataset cache via XMLA (if available)
Renaming the dataset (forces a new artifact ID without deletion)
Publishing to a new workspace to compare behavior
CSV ingestion consistency
Double-check if the latest week’s CSV is ever overwritten or appended in a way that could temporarily duplicate prior week values during refresh windows.
Given that deleting and re-publishing fully resolves it (temporarily), this strongly suggests state inconsistency in the dataset artifact rather than a modeling issue.
Hope this helps.
Thank you
Hi v-echaithra,
I tried all your suggestions, but none helped so far.
Date tables:
Here is how my date tables are set up:
Granularity column is used in report slicers and has a 1:n relationship (columns Granularity) with
Timespan column is used in report slicers and has a n:1 relationship (date_id -> id) with
which has a 1:n relationship with the fact table (which contains facts aggregated by month and by week - the bug only occurs with the weekly data).
Data types and sorting behavior:
All relevant columns have text data type. There is a dedicated sort column (timespan_sort) to properly sort the weeks and months.
Duplicate keys / granularity:
I couldn't find any issues here. No data is duplicated.
Measure logic vs implicit aggregation:
The issue occurs in all visuals, with implicit SUM aggregations as well as with explicit measures.
Service-side caching artifacts:
XMLA is not available. We have a test report in a different workspace, it has the same issue. Renaming the dataset did not fix it.
CSV ingestion consistency:
We have one csv file per week and per month which are written daily to AWS s3 storage. The refresh is triggered via API once all new files have been written.