Despite Power BI’s prowess as a leading BI tool, it inherently lacks native write-back capability. Write-back is crucial for dynamic planning and processing within companies, allowing users to adjust and save changes directly within their BI tool, affecting the underlying data source. This article explores two approaches to implementing write-back functionality in Power BI for Microsoft Fabric’s OneLake: focusing on Power Automate and the use of an intermediate transitional database.
The write-back functionality allows users to adjust and update data within Power BI, which then reflects in the underlying data source. This is particularly important for planning, forecasting, and what-if analysis, allowing for a more agile data management and planning process.
Several vendors have emerged as leaders in providing write-back extensions for Power BI, including Power ON (now Insightsoftware), InfoRiver, Acterys and deFacto Global.
These solutions extend Power BI’s functionality, enabling users to manipulate data directly from Power BI reports.
Leveraging Power Automate for Write-back
One viable method to achieve write-back to OneLake in Microsoft Fabric is through Power Automate. This process involves creating a flow that triggers on specific actions within Power BI, such as updating a field or creating a comment.
The flow then processes the input data and writes it back to the designated data warehouse in OneLake. This approach, while not direct, leverages Power Automate’s flexibility to bridge the gap between Power BI’s analytical front end and OneLake’s data storage capabilities.
Transitional Database for Data Processing
An alternative method involves using a transitional database—initially capturing write-back data in a SQL database, then transferring the updated data to OneLake. This process entails performing write-back operations on a SQL database, followed by moving the modified data to OneLake using Dataflow Gen2 or a Data Pipeline. This method effectively uses the SQL database as a transitional stage for data before it’s finalized in OneLake, addressing the direct write-back limitation in Power BI.
Explore our detailed video below, in which we demonstrate how to perform write-back to OneLake using the SQL Server as a transitional data storage.
Future Possibilities
A potential future development could see write-back vendors offering solutions that allow direct write-back to OneLake, eliminating the need for intermediary steps. While we are not aware of such technology currently available, the evolving landscape of BI tools and data management practices holds promise for more streamlined processes.
The quest for effective write-back functionality in Power BI highlights the need for innovative solutions to bridge the gap between data analysis and data management. Whether through Power Automate or utilizing a transitional database, organizations have pathways to enhance their data workflows within Microsoft Fabric’s ecosystem. As we await direct write-back capabilities, these methods stand out as critical for leveraging Power BI’s full potential alongside OneLake’s robust data storage and processing capabilities.