Making Your Power BI Teams More Analytic with Microsoft Fabric - Introduction
You spend all day helping your customers be more analytic, so why are you so unanalytic about how you run your data analytics teams? This aphorism has stuck with me since I first read it years ago in the DataOps Cookbook.
I’ve strived to make my teams more analytic, but this can be a challenge with Power BI. As a frequent reviewer of Power BI semantic models and reports, I aim to answer several critical questions:
Do pending semantic model changes still adhere to the best practices my team has set?
Do pending report changes still adhere to the best practices my team has set?
Have any semantic model changes adversely affected a report by introducing broken visuals?
Are there recurring issues with semantic models or reports that require coaching the team or individual members to avoid?
Have the number of issues improved or worsened over time? By team member?
Answering these questions requires one crucial component: data. But how do we generate, store, and analyze the data necessary to answer these questions and make our development process more analytic?
Over the next several blog posts, I’ll introduce techniques to address these questions, and possibly ones you’re thinking of as well. This series involves integrating several open-source third-party tools and Microsoft products, including Power BI, Eventhouse, and Azure DevOps. To make it manageable, I’ve broken it into the following series:
Making Your Power BI Teams More Analytic with Microsoft Fabric
- Introduction
- The Foundation
- Tracking Changes
- Report - Static Analysis
- Semantic Model - Static Analysis
- Real-time Analytics - Medallion Architecture
- Build Validation/Pull Requests
- Analyzing Results
- Report - Dynamic Analysis
- Semantic Model - Dynamic Analysis
I hope you find this series helpful in making your teams more analytic. Up next: The Foundation.
As always, let me know your thoughts on LinkedIn.