How do you handle data refresh in Power BI, and what is incremental refresh?

Scheduled refresh re-runs the queries in a published dataset on a timetable. On shared capacity you get up to eight refreshes a day; on Premium, up to forty-eight.

The on-premises data gateway is required for any source that is not cloud-accessible — an on-premises SQL Server, a file share, or a database behind a firewall. It should be installed in standard mode on a server rather than personal mode on someone's laptop, and clustered for redundancy.

Incremental refresh solves the problem of a growing fact table. Instead of reloading everything, you partition the table by date and refresh only the recent partitions.

You configure it with two parameters, RangeStart and RangeEnd, used to filter in Power Query, then set a policy such as "store 5 years of data, refresh the last 10 days".

Why it matters: a refresh that took two hours reloading five years of history can drop to two minutes. It also reduces load on the source and makes datasets larger than would otherwise be refreshable practical.

Note: Two practical points. Query folding is essential — the date filter must be pushed down to the source as a WHERE clause, and if the transformation breaks folding, incremental refresh gives no benefit. And handle late-arriving data deliberately: if records can be backdated beyond your refresh window, they will be missed, so either widen the window or trigger a full refresh periodically.