Difference between Incremental Refresh and Scheduled Refresh in Power BI
Scheduled Refresh
- Definition: A process that refreshes the entire dataset at scheduled intervals (daily, hourly, etc.).
- How it works: Every time the refresh runs, Power BI re-queries the source and reloads all the data into the dataset.
- Use case: Best for small-to-medium datasets where full refreshes are manageable.
- Limitations:
- Can be slow for large datasets.
- Consumes more resources since all data is reloaded.
- Not ideal for historical data that rarely changes.
Incremental Refresh
- Definition: A more advanced refresh strategy that only refreshes new or changed data (recent partitions), while keeping historical data static.
- How it works:
- You define policies (e.g., refresh last 3 months, keep 5 years of history).
- Power BI refreshes only the recent partitions (e.g., last 3 months) and leaves older partitions untouched.
- Use case: Best for large datasets (millions of rows) where most historical data doesn’t change.
- Advantages:
- Faster refresh times.
- Reduced load on data sources.
- Efficient handling of big data scenarios.
Comparison Table
| Feature | Scheduled Refresh | Incremental Refresh |
|---|---|---|
| Scope | Entire dataset | Only recent partitions |
| Performance | Slower for large datasets | Faster, optimized |
| Resource Usage | High | Lower |
| Best For | Small/medium datasets | Large datasets with stable history |
| Setup | Simple (just schedule) | Requires defining refresh policy |
In short
- Scheduled Refresh = refresh everything, simple but resource-heavy.
- Incremental Refresh = refresh only what’s new/changed, efficient for large datasets.
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