Havens Consulting
Video by: Reid Havens
Here's something that trips up a lot of Power BI developers: not everything belongs in your core semantic model. Some objects are meant to live in a departmental layer. Some belong in a single report, knowing the difference changes how you build, and how well your architecture holds up over time.
In this video I walk through Power BI's extensibility layer objects: what they are, where each one belongs in your architecture, and when to actually use them.
Video by: Reid Havens
Report-scoped measures (aka report-specific measures) are one of the easiest ways to level up a Power BI report without turning your semantic model into a junk drawer.
In this video, I walk through my Visual & Report-Scoped Measures guide and show the art of the possible. No deep DAX theory, no data engineering detours, just practical patterns you can steal immediately.
We’ll cover:
What “report-scoped” measures are (and when you should use them)
Six practical patterns for enhancing report UX with measures
Dynamic titles that respond to context
Conditional formatting driven by measures (so visuals explain themselves)
How to keep your model clean while still making reports more interactive and readable
If you build reports for humans (not just for your own amusement), this is a strong set of patterns to have in your toolkit.
March 6th - 9:30 AM (Pacific Time)
You’ve already invested in a Power BI semantic model. Cool. Now let’s actually use it outside the walls of a closed BI environment. In this session, Adam Schroeder (Plotly) shows how Plotly Studio can connect directly to your existing Power BI semantic model so you can build polished, production-ready data apps, powered by Python and accelerated with AI, without rebuilding or migrating your data.
You’ll learn how to:
Build fully customized, production-ready data apps using Python (beyond drag-and-drop limits)
Distribute apps broadly without getting crushed by per-user viewer licensing costs
Own your branding, UX, and deployment strategy end-to-end
Take a practical step toward operationalizing trustworthy AI on top of governed data
If you’re hitting the ceiling on Power BI customization, navigating licensing-based scaling challenges, or looking for more control over how insights (and AI) reach users, this is your playbook.
Adam Schroeder is a Senior Developer Advocate at Plotly. He has helped grow the community through 1:1 relationships, contributing to 6 million Dash downloads per month. He’s taught Plotly Dash for over five years on YouTube as @CharmingData (over 60,000 views/month) and co-authored “The Book of Dash.”
Video by: Reid Havens
Power BI reports quietly accumulate junk. Duplicate images. Orphaned files. Saved DAX and TMDL scripts that were never meant to ship.
In this video, I walk through the Report Cleanup enhancements in AE Power BI Multi-Tool Suite v2.0, focusing on how the tool helps you clean development artifacts safely and measurably before publishing.
You’ll see how the tool:
Detects duplicate images using MD5 hashing and consolidates references
Finds and removes unused and orphaned images across PBIP files
Cleans up saved DAX queries and TMDL scripts left behind by Desktop tooling
Reports exact size savings so you know what you actually gained
These are artifacts created during real development workflows. They’re invisible in Desktop, but they absolutely matter for repo hygiene, file size, and long-term maintainability.
This is about shipping cleaner, leaner Power BI reports without guessing or manually editing JSON files like a raccoon in a data dumpster.
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Reid Havens’ early love affair with analytics has, over the past decade, turned into an evolution into data visualization and report design in Power BI.
Since then Reid has been writing articles and creating YouTube videos to share the word of BI, helping to inspire the next generation of Business Intelligence enthusiasts.
