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technologyreview.com·1h ago
Data Science
Towards AI·Jun 9·5 min read
Why I Stopped Writing “Best Practice” DAX Posts (And What I Write Instead)
TL;DR
Many DAX (Data Analysis Expressions) posts focus on 'best practices' that can be misleading or overly simplistic. Instead, the author emphasizes sharing real-world experiences and practical applications of DAX in business intelligence.
✦ Why It Matters
Engineers and researchers should prioritize sharing practical experiences over generic best practices to enhance learning and application.
Key Takeaways
- Focus on practical applications of DAX in real scenarios.
- Share case studies to illustrate complex concepts.
- Engage clients with relatable challenges and solutions.
- Prioritize actionable insights over generic advice.
Full Summary
For over 20 years, the author has been involved in consulting and writing about DAX, a formula language used in Microsoft Power BI and other tools for data modeling. Initially, the focus was on 'best practices,' which often failed to address the complexities of real-world scenarios.
By transitioning to sharing practical experiences and case studies, the author has provided more relevant and actionable insights. This approach has resulted in better client engagement and satisfaction, as clients can relate to the challenges and solutions presented.
The methodology includes analyzing specific business cases and demonstrating how DAX can be effectively applied. The findings indicate that practical examples resonate more with users than generic best practices, leading to improved understanding and application of DAX in various contexts.