In a previous webinar we showed how Inforiver Enterprise adds powerful rolling forecasting capabilities to Power BI. This brings Excel-like ease of use and flexibility to the more structured, performant Power BI realm. But up to now, to fully unlock these capabilities, you had to make significant technical investments or accept performance limitations. Organizations had to navigate the tradeoff between designing complex composite models and refresh processes or limiting themselves to the slower Direct Query mode.
With the release of Microsoft Fabric, you can have your cake and eat it too! Fabric brings a new storage mode for Power BI semantic models called Direct Lake, which provides the best of Import and Direct Query modes. With Direct Lake mode, we get the performance of Import and the real-time quality of Direct Query. Direct Lake is just one of many features of Fabric that will have a positive impact on your Power BI experience.
In this webinar, discover how you can read and write data back and forth between Power BI and Microsoft Fabric’s OneLake, via Lakehouse, Data Warehouse, or Microsoft Dataverse using Inforiver’s built-in writeback engine
Watch a LIVE DEMO of Power BI recursive writeback with Fabric:
1. Writing back to Fabric Lakehouse
2. Writing back to Fabric Data Warehouse
These demonstrations will showcase recursive writeback, meaning that data written back using the Inforiver visual will be added to the semantic model and displayed in other visuals after the writeback operation is complete, without requiring further orchestration or actions from the end user.
Who should watch this webinar:
We have covered the following scenarios in this webinar:
NOTICE TO ALL PUBLIC SECTOR OR STATE-OWNED ENTITY EMPLOYEES
– Federal [including Military], State, Local and Public Education. This is a Microsoft partner event. Should items of value (e.g. food, promotional items) be disbursed to event participants, these items will be available at no charge to attendees. Please check with your ethics policies before accepting items of value.
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