Power BI is turning 10, and we’re marking the occasion with a special community challenge. Use your creativity to tell a story, uncover trends, or highlight something unexpected.
Get startedJoin us for an expert-led overview of the tools and concepts you'll need to become a Certified Power BI Data Analyst and pass exam PL-300. Register now.
Good afternoon,
I have a set of workspaces that I created for the purpose of housing my Dataflows; one for dev, test, and prod. Is there any reason why I would want to set up the dataflows into a Deployment Pipeline? I wouldn't want to overwrite the Dataflows in Deployment Pipelines, so what is the purpose?
For example: my Dev database is pointed to my Test and Dev workspaces, and my Prod database is pointed to my Prod workspace. Therefore if the workspaces were in a deployment pipeline, wouldn't my Prod workspace just get overwriten with the Dev configuration?
Solved! Go to Solution.
In a deployment pipeline, you can set rules for the data source and parameters for each dataset. So when you deploy from test to pre-prod to prod, you can change the connection string for the database connection.
In a deployment pipeline, you can set rules for the data source and parameters for each dataset. So when you deploy from test to pre-prod to prod, you can change the connection string for the database connection.
How would you actually go about doing this? When I look in the deployment rules, the "Data Source Rules" are greyed out. So its a bit confusing to me. It says I can go to "artifact settings" to change the data source settings, but when I go there, I don't see an option to change the actual data source.
Thank you, I'm going through that process and I do see those options. Looks like its asking me to modify the settings from the artifact settings. Will go through this process and see how it works. thanks!
This is your chance to engage directly with the engineering team behind Fabric and Power BI. Share your experiences and shape the future.
Check out the June 2025 Power BI update to learn about new features.
User | Count |
---|---|
56 | |
27 | |
26 | |
22 | |
20 |
User | Count |
---|---|
58 | |
45 | |
24 | |
24 | |
18 |