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gloulakis
Regular Visitor

Need Guidance on Exporting Large Dataset from Fabric Report

I’m working on a report in Microsoft Fabric, and I need to export around 1 million rows and 600 columns to Excel.

What’s the best way to achieve this, considering the current platform limitations? Are there any workarounds or recommended practices for exporting large datasets?

Thank you in advance for your help!

1 ACCEPTED SOLUTION

Hi @gloulakis ,

Thanks for reaching out to the Microsoft fabric community forum. 

 

Can you please try below options:
1. Use a Paginated Report: Paginated reports can handle large tables. You can publish the paginated report to Fabric and export directly to Excel or CSV.

How to: Use Power BI Report Builder to create the paginated report. Connect to your Fabric dataset or a shared semantic model. Export the full table.

Note: Use CSV if Excel runs into memory issues.

2. Use Dataflows or Notebooks to Export to OneLake or Azure: If your data model is backed by a Lakehouse or Warehouse in Fabric: Use a Notebook (Spark or SQL) to extract the data into CSV or Parquet files in OneLake. From there, download the file or import into Excel.

Advantages: No export limit, flexible output, better for automation.

3. Use DAX Studio or Tabular Editor for Direct Export: Connect to your Fabric semantic model using DAX Studio. Run a DAX query to pull your table and export to CSV. Much faster and bypasses Power BI export limitations.

4. Break It Down into Chunks: Create filters or slicers in your report to break the export into manageable pieces (e.g., by month or BU).Export chunks manually or automate with Power Automate (if feasible).

Note: Excel is not ideal for handling 1M rows × 600 columns. Consider using Parquet or CSV format and tools like Python, R, or Power Query for downstream analysis. Try Power BI Dataflow Gen2 to export the data to a Lakehouse, which integrates easily with Fabric and has no export limits. Consider using Azure Data Factory or Logic Apps if you need to automate large data movements out of Fabric.

 

If you find this post helpful, please mark it as an "Accept as Solution" and consider giving a KUDOS. Feel free to reach out if you need further assistance.
Thanks and Regards

 

View solution in original post

4 REPLIES 4
Akash_Varuna
Super User
Super User

Hi @gloulakis There are limitations in exporting large datasets from Fabric to Excel. To work around this, consider exporting to CSV, which handles larger datasets, or use paginated reports for better export flexibility. If you could then also try to export the data to Azure SQL Database or Blob Storage for processing. For Excel-specific needs, split the dataset into multiple files or connect directly via "Analyze in Excel."

Hi @gloulakis ,

Thanks for reaching out to the Microsoft fabric community forum. 

 

Can you please try below options:
1. Use a Paginated Report: Paginated reports can handle large tables. You can publish the paginated report to Fabric and export directly to Excel or CSV.

How to: Use Power BI Report Builder to create the paginated report. Connect to your Fabric dataset or a shared semantic model. Export the full table.

Note: Use CSV if Excel runs into memory issues.

2. Use Dataflows or Notebooks to Export to OneLake or Azure: If your data model is backed by a Lakehouse or Warehouse in Fabric: Use a Notebook (Spark or SQL) to extract the data into CSV or Parquet files in OneLake. From there, download the file or import into Excel.

Advantages: No export limit, flexible output, better for automation.

3. Use DAX Studio or Tabular Editor for Direct Export: Connect to your Fabric semantic model using DAX Studio. Run a DAX query to pull your table and export to CSV. Much faster and bypasses Power BI export limitations.

4. Break It Down into Chunks: Create filters or slicers in your report to break the export into manageable pieces (e.g., by month or BU).Export chunks manually or automate with Power Automate (if feasible).

Note: Excel is not ideal for handling 1M rows × 600 columns. Consider using Parquet or CSV format and tools like Python, R, or Power Query for downstream analysis. Try Power BI Dataflow Gen2 to export the data to a Lakehouse, which integrates easily with Fabric and has no export limits. Consider using Azure Data Factory or Logic Apps if you need to automate large data movements out of Fabric.

 

If you find this post helpful, please mark it as an "Accept as Solution" and consider giving a KUDOS. Feel free to reach out if you need further assistance.
Thanks and Regards

 

Hi @gloulakis ,

If you find this post helpful, please mark it as an "Accept as Solution" and consider giving a KUDOS. Feel free to reach out if you need further assistance.
Thanks and Regards

Hi @gloulakis ,

If you find this post helpful, please mark it as an "Accept as Solution" and consider giving a KUDOS. Feel free to reach out if you need further assistance.
Thanks and Regards

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