This session explores practical tips for writing and testing DAX measures using the new Copilot integration and the DAX Query View. Mitchell Pearson demonstrates real-world examples of visual calculations, measure lineage, and the benefits and limitations of using AI assistance in DAX development.
Key Highlights
- Visual Calculations: Greg Treziac shows how to add custom visuals with emoji indicators for better readability and dynamic formatting.
- DAX Query View: Understand the power of testing and validating measures without committing changes. This helps debug complex measure chains with full lineage visibility.
- Copilot in Power BI: Mitchell demonstrates how Copilot can generate DAX measures for tasks like prior week sales, period-over-period comparisons, and top/bottom product sales, saving time on repetitive coding.
What Works Well
- Copilot can provide a strong starting point for DAX logic based on your model.
- It explains complex functions like
TREATAS() in plain language, which is helpful for learning.
- Using DAX Query View, you can test changes safely before saving them to your model.
Limitations to Watch Out For
- Copilot’s DAX suggestions aren’t always accurate. Some generated measures can return incorrect results, especially when date contexts vary (e.g., period-over-period calculations).
- Always validate AI-generated measures at multiple hierarchy levels (week, month, quarter) to avoid silent errors.
- Good data modeling remains crucial — Copilot can’t fix underlying model issues.
Key Takeaway
Copilot is a powerful accelerator for DAX development, but it’s not a replacement for solid DAX skills. Always test and validate your calculations thoroughly. Combining Copilot with a robust data model and the DAX Query View will help you build accurate and efficient reports in Power BI.
Final Thoughts
Adopting Copilot and other AI tools can boost your productivity as a Power BI developer — but they work best when paired with careful review and a clear understanding of DAX fundamentals.
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