Episode 295 – Power BI May 2025: Copilot Takes Center Stage & Transactional Task Flows Arrive

Fresh off their successful workshop tour in Germany (complete with Jason’s ambitious schnitzel consumption), John and Jason dove into the Power BI May 2025 feature summary—a release packed with preview features that signal major shifts in how users interact with their data.

The New Fabric Roadmap Tool

Before jumping into features, the duo highlighted a crucial new resource: the Fabric Roadmap tool at https://roadmap.fabric.microsoft.com (or https://aka.ms/fabricroadmap). This replaces the old wave documents and provides transparency about upcoming features, release dates, and status. While not comprehensive—it focuses on major committed features—the tool offers valuable planning insights. John noted the team’s willingness to share dates they’re confident hitting, a refreshing approach to product roadmaps.

Copilot Gets Its Own Home

The biggest architectural change? Copilot now exists as a standalone experience in Power BI, accessible directly from the left rail. Think of it as “Search Plus”—a main page similar to the Microsoft 365 copilot interface where users can ask questions, request reports, and get summaries across their entire data estate.

Jason expressed mixed feelings about this approach, comparing it unfavorably to the recent office.com changes that buried familiar navigation behind a chat interface. “Just because you can doesn’t mean you should,” he quipped, though he acknowledged this implementation works better than the M365 version since it doesn’t replace existing navigation.

The key difference from traditional search? Copilot returns authoritative answers rather than multiple options. As John put it, “when it’s wrong, it’s authoritatively wrong”—no thesaurus-style alternatives appear. The system uses linguistic understanding to interpret queries contextually, eliminating the need for precise phrasing that plagued earlier Q&A implementations.

Prepping Data for AI Success

With Copilot’s expanded role comes increased emphasis on data preparation. A new ribbon button helps users optimize semantic models for AI through three mechanisms:

  • AI Data Schema: Flag specific columns/measures for AI to consider, filtering out noise
  • Verified Answers: Create phrase-based Q&A pairs with defined DAX responses—an evolution of the old synonyms feature
  • AI Instructions: Provide specific guidance about data handling and exclusions

The duo questioned whether users would actually invest time in this prep work. Jason admitted he’s never worked on a project that implemented synonyms, despite seeing their value. “In the historical use of synonyms, it was never something we got around to,” he noted. John countered that within Fabric’s broader context—where AI extends beyond just reports—the compelling reasons to prep data multiply significantly.

Transactional Task Flows: The Write-Back Revolution

Perhaps the most significant new capability: transactional task flows enable write-back functionality in Power BI through Fabric’s user-defined functions (UDFs). While Power BI itself remains read-only, users can now trigger actions filtered to their current report context—actions that can write data, interact with third-party systems, or execute complex workflows.

Jason’s spending two days focused on this feature, seeing it as a potential replacement for Power Apps integrations in many scenarios. The approach keeps everything within Fabric, reducing threat surfaces and boundary crossings. However, John emphasized that Power Apps still excel for mobile-first scenarios requiring field interaction.

Common use cases include budgeting tools where users adjust growth percentages and save scenarios, or approval workflows that update backend systems. The key requirement? You need Fabric capacity and UDFs—this isn’t available in standalone Power BI.

Everything’s in Preview

A running joke throughout the episode: nearly every feature discussed exists in preview. From the roadmap tool to copilot enhancements, transactional task flows to Direct Lake improvements—May’s release reads like a preview showcase. John and Jason repeatedly reminded listeners to enable preview features in options and settings.

Other Notable Updates

The duo covered several additional improvements:

  • Persistent Sorting for Field Parameters: Sort orders now persist when switching between dimensions (though John questioned the use case)
  • Visual Calculations Lookup Functions: New functions for referencing specific values across contexts
  • List Slicer Enhancements: Images in slicers, paste-in filtering from Excel, and restricted leaf nodes
  • Line Chart Color Customization: Now generally available, joining the “didn’t know you couldn’t do that” department
  • Azure Maps Visual Improvements: Country/state/county borders, building and road details, plus new data privacy controls
  • Tabular Editor View Upgrades: Better tooltips, automatic formatting, easier column renaming with source tracking
  • Direct Lake + Import Hybrid Models: Mix storage modes in the same semantic model (desktop only, no live editing yet)

The Germany Experience

Between feature discussions, Jason and John shared highlights from European Collaboration Summit in Düsseldorf: nearly 3,000 attendees across business apps, data, and cloud tracks; eight food trucks serving fresh lunches; excellent audience engagement during their three sessions plus full-day tutorial on source control in Fabric. The event moves to Cologne in early May 2026, conveniently timed for Jason to attend after his son’s graduation.

Looking Ahead

With Microsoft Build occurring during May, the release predictably packed more preview features than usual. The Fabric feature summary promises to be even larger, likely requiring multiple episodes to cover properly.

For now, May’s Power BI updates signal a clear direction: AI-powered interactions moving to the forefront, true transactional capabilities arriving through Fabric integration, and continued refinement of Direct Lake authoring experiences. Whether users invest time in AI data prep and adopt these new workflows remains to be seen—but the capabilities now exist for those ready to explore them.


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