Forum Discussion
Unable to Read Fabric Warehouse/Lakehouse DACPAC using Notepad or any Editor
- 7 months ago
Hi yashaswi_raj ,
Thanks for reaching out to Community Forum.This is expected behavior and not an issue with Microsoft Fabric. A DACPAC exported from a Fabric Warehouse or Lakehouse is not a plain text file, so opening it in Notepad will always look unreadable. In Fabric, a DACPAC represents a packaged database schema that is meant to be consumed by supported tools, not viewed directly as text. The correct way to inspect or work with it is to import it into a SQL Database Project (for example using Visual Studio or Azure Data Studio) or use SqlPackage to extract or deploy the schema. This confirms that the export itself is valid the limitation is simply that Notepad cannot interpret the DACPAC format.
Supporting Fabric documentation :
https://learn.microsoft.com/en-us/fabric/database/sql/overview
https://learn.microsoft.com/en-us/fabric/database/sql/sqlpackage
https://learn.microsoft.com/en-us/fabric/data-warehouse/develop-warehouse-project
Thank you.
Hi yashaswi_raj ,
I would take a moment to thank deborshi_nag , for actively participating in the community forum and for the solutions you’ve been sharing in the community forum. Your contributions make a real difference.
I wanted to check if you had the opportunity to review the information provided. Please feel free to contact us if you have any further questions
hi v-sshirivolu , the solution looks overwhelming , can you tell me what at present is the industry accepted way of deploying the warehouse ?
- v-sshirivolu7 months agoCommunity Support
Hi yashaswi_raj ,
The industry accepted approach is to deploy Fabric Warehouses using DACPAC based CI/CD pipelines, similar to how Azure SQL is deployed. The DACPAC is treated purely as a deployment artifact and isn't intended to be read or edited manually. Any schema comparison or incremental changes are handled using supported tools like SqlPackage or SQL Database Projects, rather than by inspecting the DACPAC file itself. This approach helps keep deployments consistent, supported, and repeatable across different environments.