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Hi,
with incremental refresh you can define a date column (last_updated for example) if you have and set up a look-back window (i.e. 30 min), that will re-read only the data changed in the last 30 minute.
So if you have a row that was older than 30m min but updated in the window it will be captured and added, the caveat is that when Quicksight tries to remove all the record in the incremental windows it will not find the older record, and you will end up with some duplicates.
Still, it is possible to avoid issue for the visuals by adding a calculated measure in Quicksight using the runningcount function partitioned by the unique key of the record and ordered by the last modified date descending (the one used in the incremental refresh) , then set a filter on that calculated columns that is equal to 1 and apply the filter to all visuals . The filter will keep only the most recent value making the dashboard correct.
The duplicates can be removed with a full refresh, and you can also set up an alert to know whenever a duplicate is added in the Spice dataset, so that a full refresh could be submitted.
Hope this helps
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