Forum Discussion
Need help: Merging multiple reports data into one central database in PowerBI service
HI Tutu_in_YYC ,
1.Dataflow uses Power BI internal storage to store data by default, and does not enforce Azure Data Lake Storage Gen2 access.Gen 1 you only need to have Pro access or PPU access, but you encounter (store large amounts of data or cross-service integration), only to use to Azure Gen 2, for most of the For most scenarios, the built-in storage is sufficient.
Configure and consume a dataflow - Power BI | Microsoft Learn
2. Regarding the DAX computation of Dataflow data after it enters the semantic model, your understanding is absolutely correct! Dataflow is responsible for providing the cleaned and processed data to the semantic model. In the semantic model, you can centrally create and manage DAX metrics, and these metrics can be reused by multiple reports. If you update DAX calculations in the semantic model, all reports that rely on the model automatically apply the updates, simplifying the management process.
3. Dataflow is well suited to handle data from SQL Server and Excel files. Its ability to unify the processing of this data makes it suitable for building centralized data models. If you don't need to use Azure Data Lake Gen2, Dataflow doesn't come at an additional cost and you can use the storage built into Power BI.Hope it helps!
Best regards,
Community Support Team_ Tom ShenIf this post helps then please consider Accept it as the solution to help the other members find it more quickly.
Hi ALL,
Firstly Tutu_in_YYC thank you for your solution!
And lszymk97 , If you want to create a Central Data Model, you can try Dataflow in Power BI Service, which provides a centralized ETL (Extract, Transform, Load) platform that allows you to integrate data from different reports into a central data structure.Dataflow can be provided as a data source to multiple Power BI reports in the Power BI service, and multiple reports can share the same central data model by connecting to the same Dataflow. This avoids duplicate data extraction and processing and ensures that all reports use the same, uniform data.
Introduction to dataflows and self-service data prep - Power BI | Microsoft Learn
You can refer to the figure below, where we first consolidate all the data into a central dataset, clean it up, and then go back to Power BI desktop to define the relationships between the different tables (e.g., joining a fact table to a dimension table), and then publish it as a shared dataset to be used by other reports.
I hope my answer can help you solve the problem, if you have further questions, you can contact me at any time, I will be the first time to reply to you after receiving your message!
Hope it helps!
Best regards,
Community Support Team_ Tom Shen
If this post helps then please consider Accept it as the solution to help the other members find it more quickly.
Thank you for your reply I think I will flag it as a solution. But I have couple of questions: 1) would dataflow require azure gen2 Access? 2) I understand that data from dataflow would go into one semantic model where we could bulk update our DAX measures for different reports pulling the data from this semantic model? 3) Also, we have a ms sql database with excel files mainly, do you think dataflow is correct for these bearing in mind additional costs coming from having gen2 dataflow in Azure.
Thanks,
Lukasz
HI Tutu_in_YYC ,
1.Dataflow uses Power BI internal storage to store data by default, and does not enforce Azure Data Lake Storage Gen2 access.Gen 1 you only need to have Pro access or PPU access, but you encounter (store large amounts of data or cross-service integration), only to use to Azure Gen 2, for most of the For most scenarios, the built-in storage is sufficient.
Configure and consume a dataflow - Power BI | Microsoft Learn
2. Regarding the DAX computation of Dataflow data after it enters the semantic model, your understanding is absolutely correct! Dataflow is responsible for providing the cleaned and processed data to the semantic model. In the semantic model, you can centrally create and manage DAX metrics, and these metrics can be reused by multiple reports. If you update DAX calculations in the semantic model, all reports that rely on the model automatically apply the updates, simplifying the management process.
3. Dataflow is well suited to handle data from SQL Server and Excel files. Its ability to unify the processing of this data makes it suitable for building centralized data models. If you don't need to use Azure Data Lake Gen2, Dataflow doesn't come at an additional cost and you can use the storage built into Power BI.Hope it helps!
Best regards,
Community Support Team_ Tom ShenIf this post helps then please consider Accept it as the solution to help the other members find it more quickly.
