Question
You use a dataflow to import data into Microsoft Dataverse.
The data uses the following schema:
| Column name | Data type |
|---|---|
| accountid | Unique Identifier |
| accountnumber | Text |
| createdon | Date and Time |
| modifiedon | Date and Time |
| versionnumber | Big Integer |
The data must load in the least amount of time.
You need to configure the incremental refresh settings for the dataflow.
Which columns should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Explanation
Filter field: createdon — Incremental refresh in a Power Platform dataflow requires a DateTime column to slice the source data into time-based partitions (for example, "refresh rows from the last N days"), and createdon is the Dataverse system DateTime column that records when each row first entered the table, so it correctly defines which rows belong to which historical range. accountid and accountnumber are identifier columns, not date/time values, so they cannot be used as the range filter, and versionnumber is a BigInt row-version value rather than a date, so it is also unusable here.
Detect data changes: modifiedon — When "Detect data changes" is enabled, the dataflow compares the maximum value of the chosen DateTime column per partition against the previous run and reloads only the partitions where that value has increased, which is what keeps the load time to a minimum. modifiedon is updated by Dataverse every time a row is changed, so it accurately signals which partitions contain updates; createdon would never change for existing rows and would therefore miss edits, while accountnumber and versionnumber are not DateTime columns and are not valid selections for this setting.
