Refresh Performance with Snowflake

[manoj_0911]

Are there recommended Power BI settings for optimizing refresh performance when importing large datasets from Snowflake?

[Natarajan_M · Accepted solution]

Hi @manoj_0911 If your question is about improving the refresh performance in general, then you can check the below .

1. Query folding -> ensure that your query is getting folded for each table
2. Bring only necessary columns from the source 
3. Push the transformation to the Source side , avoid implementing transformations in the PQ layer / Dax layer e.g calculated columns 
4. Implement incremental refresh where ever possible 
5. If you can add the fact tables in Direct query mode and the create a user managed aggreagates (in incremental refresh)
6. Take care of the normal design standards data type and precesions like keep data time as date if the time is not helpfull , use integer for joins etc
7. enable large model in service and query scaling 

Thanks 

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[v-hashadapu]

Hi @manoj_0911 , Hope you are doing well. Kindly let us know if the issue has been resolved or if further assistance is needed. Your input could be helpful to others in the community.

[v-ssriganesh]

Hi @manoj_0911,

Thank you for posting your query in the Microsoft Fabric Community Forum, and thanks to @cengizhanarslan & @Natarajan_M for sharing valuable insights.

Could you please confirm if your query has been resolved by the provided solutions? This would be helpful for other members who may encounter similar issues.

Thank you for being part of the Microsoft Fabric Community.

[cengizhanarslan · Accepted solution]

1. Push transformations to Snowflake

Try to keep Power Query as simple as possible and let Snowflake do the heavy work.

Good approach:

• Use views or optimized SQL queries in Snowflake

• Avoid complex transformations in Power Query

 

2. Use Incremental Refresh

For large tables, this is usually the biggest performance improvement.

Configure incremental refresh with parameters such as: "RangeStart", "RangeEnd"

3. Ensure query folding

Power BI should push filters and transformations back to Snowflake. In Power Query: "Right click step → View Native Query". If folding is broken early, Power BI may pull large datasets locally before processing.

4. Reduce imported data

Only import what you actually need:

• remove unused columns

• filter historical data

• avoid importing high-cardinality text columns when unnecessary

Reducing data size improves both refresh time and model compression.

5. Avoid unnecessary table relationships during load

Large models with many relationships can slow processing.

• prefer star schema

• avoid complex many-to-many relationships

• use surrogate keys when possible

[Natarajan_M · Accepted solution]

Hi @manoj_0911 If your question is about improving the refresh performance in general, then you can check the below .

1. Query folding -> ensure that your query is getting folded for each table
2. Bring only necessary columns from the source 
3. Push the transformation to the Source side , avoid implementing transformations in the PQ layer / Dax layer e.g calculated columns 
4. Implement incremental refresh where ever possible 
5. If you can add the fact tables in Direct query mode and the create a user managed aggreagates (in incremental refresh)
6. Take care of the normal design standards data type and precesions like keep data time as date if the time is not helpfull , use integer for joins etc
7. enable large model in service and query scaling 

Thanks 

If this response was helpful in any way, I’d gladly accept a kudo.
Please mark it as the correct solution. It helps other community members find their way faster