Don't miss your chance to take the Fabric Data Engineer (DP-700) exam on us!
Learn moreNext up in the FabCon + SQLCon recap series: The roadmap for Microsoft SQL and Maximizing Developer experiences in Fabric. All sessions are available on-demand after the live show. Register now
Hello experts,
I've come across an issue where I've identified duplicate tables in different domains, such as Finance and Supply Chain. I know which domain each table should rightfully belong to. The challenge arises because these tables are linked to Power BI reports. My concern is how to proceed without causing disruptions. Let's say, for instance, I've found that the MARC table exists in both Finance and Supply Chain, but I've decided it should only be associated with Supply Chain. This decision could potentially break the reports connected to Finance. Is there a way to guide Power BI to automatically locate the correct path to the table, given that its name remains unchanged? Naturally, I would ensure that access rights to the Supply Chain domain are properly set up.
Solved! Go to Solution.
Hi @Anonymous ,
Hope all is going well.
For the same data source, as long as the connection name and verification are the same, only one data source will be displayed. If the next referenced table is the same as the previous verification, there is actually only one data source.
Therefore, changes cannot be made through Change Data Source.
Alternatives are:
Create multiple dataflow, put the tables related to Finance in one dataflow, and put the tables related to Supply Chain such as MARC in another dataflow. Create a semantic model based on the dataflow, and then use the data to create reports.
For relevant documentation on dataflow, please refer to the link below:
Creating a dataflow - Power BI | Microsoft Learn
Configure and consume a dataflow - Power BI | Microsoft Learn
If you have any further questions please feel free to contact me.
Best Regards,
Yang
Community Support Team
If there is any post helps, then please consider Accept it as the solution to help the other members find it more quickly.
If I misunderstand your needs or you still have problems on it, please feel free to let us know. Thanks a lot!
Hi @Anonymous ,
Hope all is going well.
For the same data source, as long as the connection name and verification are the same, only one data source will be displayed. If the next referenced table is the same as the previous verification, there is actually only one data source.
Therefore, changes cannot be made through Change Data Source.
Alternatives are:
Create multiple dataflow, put the tables related to Finance in one dataflow, and put the tables related to Supply Chain such as MARC in another dataflow. Create a semantic model based on the dataflow, and then use the data to create reports.
For relevant documentation on dataflow, please refer to the link below:
Creating a dataflow - Power BI | Microsoft Learn
Configure and consume a dataflow - Power BI | Microsoft Learn
If you have any further questions please feel free to contact me.
Best Regards,
Yang
Community Support Team
If there is any post helps, then please consider Accept it as the solution to help the other members find it more quickly.
If I misunderstand your needs or you still have problems on it, please feel free to let us know. Thanks a lot!
You can manually rewrite the source using the Advanced Editor in Power Query (assuming they are both in the same database/source) or select the specific data location on the first step in the query by clicking the gear icon in Source. There you can select the new path. Your query won't break as long as this "new table" has the exact same structure as the previous one.
Proud to be a Super User!
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.
Share feedback directly with Fabric product managers, participate in targeted research studies and influence the Fabric roadmap.
| User | Count |
|---|---|
| 56 | |
| 47 | |
| 44 | |
| 20 | |
| 20 |
| User | Count |
|---|---|
| 73 | |
| 72 | |
| 34 | |
| 33 | |
| 31 |