Building Your Power BI CI/CD Pipeline with the Best Practice Analyzer - Part 1
Why your Power BI project needs the Best Practice Analyzer (BPA)
In my previous post, I discussed the importance of version control and introduced the concept of CI/CD for Power BI. I also promised to provide a step-by-step guide on how to create a GitHub Actions workflow and use the Best Practice Analyzer. While writing that post I realized that might be too big of a jump, before going straight into the technical details, some additional explanation is needed. This will help understand the basics, avoid unnecessary issues and customize BPA to fit your specific workflow. Two key points I’ll cover before jumping into technicalities:
✅ Why BPA matters in a Power BI Project and in a CI/CD pipeline (covered in this post, Part 1)
✅ How to configure BPA effectively by choosing the right rules and severity levels (covered in Part 2)
🎯My Goal with These two Posts
My main objective is to inspire confidence and encourage you to explore this solution.
Feel free to ping me here or on Linkedin if you feel that you need a little extra nudge to start experimenting with this approach!
What You’ll learn in these posts:
Why the Best Practice Analyzer (BPA) is a powerful starting point for integrating automated checks into your CI/CD pipeline using GitHub Actions or Azure DevOps. (Part 1)
Why BPA is particularly valuable in multi-developer environments, helping teams maintain consistency and avoid common pitfalls in Power BI projects. (Part 1)
How to configure BPA rules effectively, emphasizing the importance of prioritization, team feedback, and iterative improvements to find the right balance between automation and flexibility. (Part 2)
By the end of these two posts, you'll see how BPA can genuinely make life easier and how balancing automation with trust can help your team work smarter, not harder.
Before diving into BPA, let’s first discuss why collaboration in Power BI projects can be so challenging.
Collaboration Challenges in BI Projects
If you’ve worked on a Power BI project, you know how tricky collaboration can be —even when it comes to seemingly small details:
Should your DAX formulas use spaces between operators or not?
How do you avoid the usage of multiple measures with the same DAX expression but different measure name?
How do you ensure that every measure uses the same naming convention?
These and many similar scenarios can create a minefield of potential errors and misunderstandings.
From my point of view, effective collaboration in Power BI requires:
A standard of consistency
Preventing errors
Applying standards across both small and large projects
While you want to aim for consistent quality, you also want to flag issues as early as possible, preferably through an automated process.
These challenges make collaboration difficult. Maintaining quality can feel almost impossible without a structured approach. This is where CI/CD comes in. CI/CD is not just about automating processes; it’s about creating a structured workflow that ensures collaboration remains efficient, consistent, and error-free. It’s also about creating a process where quality is maintained at every stage—automatically catching issues before they snowball into bigger problems. You can enforce a consistent set of rules, regardless of the developer’s personal preferences or beliefs.
It may sound straightforward in theory, but in reality, it’s not always so, especially when it comes to implementing these rules effectively. If you think about this question for a moment: How do we make sure that these rules are always enforced automatically? The solution may not be as straightforward anymore.
To help tackle these collaboration challenges in Power BI projects, we can integrate automated solutions into our development pipeline. Let’s dive into why BPA is a great place to start.
Why the Best Practice Analyzer (BPA) is a powerful starting point
Best Practice Analyzer (BPA) can improve automation in CI/CD. It evaluates Power BI semantic models using predefined rules, providing deeper insights into their structure and quality.
BPA helps you:
✔ Identify areas that need attention
✔ Detect questionable model components instantly
✔ Save time by catching errors even before opening Power BI Desktop
Many online resources can help you get started with BPA in Tabular Editor (which you can run on your laptop without even starting to think about CI/CD), including the official documentation or community-driven guides or a very detailed post from Nikola.
It also saves valuable time during the code review process by identifying issues before you even open Power BI Desktop. For example, BPA can automatically detect many-to-many relationships in your model, sparing you from manually hunting them down in the Model view. If you have a relatively simple model, finding a relationship like this is easy. But what if you have to review the model of your colleague you haven’t seen before and you face with a model like below. This example is a bit extreme on purpose, but it’s not too far away from reality. It would be easier to get just an automatic feedback notification after you run the BPA.
Moving to another example. When business users can interact with the report, it’s a common requirement to add description to the more complex calculated items, where developers have to pre-define the meaning of the calculation to ensure clarity and accuracy for the users. This can range from a brief summary to a more detailed explanation of the DAX logic. BPA can also list all the items without descriptions, so you don’t have to hover over all of your measures to check them.
BPA can also help you identify unused elements - even if the Measure Killer is doing a way deeper analysis on your model - this feature has already reminded me several times that a “Dummy Table” I created for experimenting was left in the model. Unused elements like this can negatively impact performance and cause confusion for other developers.
Have you ever created 2 measures with different names but the same DAX code? This redundancy can lead to confusion, as well as unnecessary complexity in your model. No problem, BPA can flag these in no time.
My last exaple is another common issue: Have you ever had a (Blank) value in a slicer, like this?
I have. And sometimes I still do if I have to work with custom dimension tables (those not existing in the DB or created manually for Excel-based reports). This can lead to unexpected results, with business users rightfully questioning the accuracy of the filters. These issues can damage trust in the reports, especially for users new to Power BI, so they are best avoided when possible. Fortunately, BPA can instantly flag this problem for you.
Beyond these specific cases, BPA also offers close to a hundred rules focusing on error prevention, performance improvements, DAX expressions, metadata, formatting, and more.
Once you run it in Tabular Editor, you’ll get a list of all the questionable parts of your model, a screen similar to this screenshot. From this point it’s up to you to handle the issues and decide if these really need your attention.
BPA, on its own, can help you become a better developer by:
Helping you follow best practices
Saving time during code reviews
Ensuring higher quality standards in team projects.
And it’s not just you who will become a better developer. If you combine the collaboration challenges in a multi-developer environment and all the issues BPA can flag it’s easy to see how BPA is an amazing tool in helping teams maintain consistency and avoid common pitfalls in Power BI projects.
When incorporated into your CI/CD pipeline, BPA also allows you to evaluate your semantic model after every change - whether it's a Pull Request, commit, or a manual trigger, depending on your preference. To this, understanding how BPA works is just the first step. The next challenge is deciding which rules matter most, and then:
How do you prioritize them?
How do you decide how strictly you want to enforce them?
In Part 2, we’ll dive into how to configure BPA to suit your team’s needs, selecting the right rules, and adjusting the severity levels to ensure BPA works the way you want it to.