Power BI incremental refresh of old updated data

Question

I'm trying to figure out if there a possibility to config incremental refresh for the old data which could be updated.

E.g. we have initial table data (Azure SQL DB as a source):

audit_date	val	updated_ts
2017-07-01 00:00:00.000	10	2017-07-01 00:00:00.000
2018-06-01 00:00:00.000	20	2018-06-01 00:00:00.000
2020-12-20 00:00:00.000	30	2020-12-20 00:00:00.000

and incremental refresh properties as below (audit_date is non-changable filtered column):

After data is published and refreshed it reflects whole source data (Power BI Pro):

Then we update some val column value (updated_ts receives current datetime value) and get below rows on the source:

audit_date	val	updated_ts
2017-07-01 00:00:00.000	10	2017-07-01 00:00:00.000
2018-06-01 00:00:00.000	555	2020-12-24 13:01:02.000
2020-12-20 00:00:00.000	30	2020-12-20 00:00:00.000

After refresh we still see initial values:

Does it mean that incremental refresh does not catch changes of old data or my understanding is wrong? Perhaps there is another way exists for such data changes handling?

Answer 1

You've limited your rows to refresh to the last 30 days according to the audit_date column. Thus the row in question outside of the scope you've set.

The official documentation makes a similar remark:

Filter date column updates

The filter on the date column is used to dynamically partition the data into ranges in the Power BI service. Incremental refresh isn't designed to support cases where the filtered date column is updated in the source system. An update is interpreted as an insertion and a deletion, not an actual update. If the deletion occurs in the historical range and not the incremental range, it won't get picked up. This can cause data refresh failures due to partition-key conflicts.