Analyst in Action

Good to be back after a short break. This is a topic I’ve personally been wanting to explore, understanding  why  and  when  we actually need different environments in Power BI. If you’re currently questioning whether it’s time to move toward Dev, Test, and Prod, this one’s for you. Let’s break it down. Imagine you’re cooking for yourself at home. You experiment freely, adjust as you go, and if the dish isn’t perfect, it’s not a big deal. Now imagine you’re cooking for a wedding with 300 guests. You don’t experiment during service. You test recipes beforehand, prepare in stages, and control every step before it reaches the table. Power BI environments work the same way. When your BI setup is small and lightly used, working directly in a single production workspace feels efficient. Changes are quick, feedback is immediate, and even if something breaks, the impact is limited. But Power BI rarely stays small. As more developers get involved, semantic models are reused a...

This is the first  Analyst in Action  post of 2026, and it starts with a problem most Power BI teams know well and still tend to avoid. Documenting a Power BI model often feels like labeling boxes while the warehouse is still being rebuilt. You might get everything neatly written down today, but by next week, half of it no longer matches what’s actually on the floor. Before long, documentation starts to feel like an admin task, and it quietly drops to the bottom of the list. In real projects, things move quickly. Measures get added late, business logic changes after stakeholders review the numbers, and datasets end up feeding far more reports than originally planned. Documentation struggles to keep up with that pace. When it exists, it’s usually manual, spread across multiple files, and already outdated by the time someone looks at it. The impact is very real. New BI developers take longer to become productive, small changes break reports in unexpected places, and important lo...

Last blog for the year! And before leading into 2026, let's talk about one of the hot topics that is always tricky to understand while working with Power BI and Fabric. On most days, your reports are running perfectly, and suddenly, you get a notification that you have consumed more than 80% of the capacity.  A report that usually opens in seconds starts taking ages to open. Visuals take longer to load. Sometimes a refresh fails with a capacity-related error. When you check the metrics, there is a sharp spike in capacity usage that wasn’t there before. What makes this frustrating is that nothing obvious changed. No new reports were deployed. No large datasets were added. Yesterday worked fine, so today  should  work fine too. The natural response is to assume the capacity is too small. If usage spiked and things broke, it feels logical to conclude that more capacity would solve the problem. This conclusion makes sense. Capacity feels like a fixed limit, and hitting that l...

" When is it time to stop copying PBIX files and start reusing a shared model?" Most BI developers begin their Power BI journey the same way: one PBIX file that does absolutely everything. It holds the data model, the queries, the measures, and all the report pages on top. It’s simple, self-contained, and easy to understand. That's normal, no? Yes, absolutely, but let's imagine a scenario where there are different teams, and they want the same dataset but tweaked in a different way for their purpose. Since your semantic model is quite big in terms of size. Generally, you can just make the adjustments and create multiple PBIX files for different audiences. This solution will work, but let's understand what we are doing. After a few months, what started as one neat, well-understood PBIX turns into a small family of very similar files: Multiple PBIX files containing almost the same model KPIs that should mean the same thing but don’t quite match A growing fear that c...

We’re back after a long break, and in the meantime, the blog has had a bit of a makeover. There’s now a curated list of posts for anyone starting their Power BI journey, so feel free to check that out if you’re new around here. Now, let’s get back to today’s topic. Think of this scenario: you’ve done all the hard work, built a clean report, everything looks perfect… and just before publishing, you pause for a second. I used to run a mental checklist every time. Do you do it too? Should you?  Honestly, yes. A simple checklist can save you from those painful “the report is broken” messages that pop up from every direction once a stakeholder opens it. I’ve been there more times than I’d like to admit, and that’s exactly why I put this list together from my mental checklist to the analyst in action blogs. It’s not theory, it’s a collection of small lessons learned from actual reports, moments of panic, and last-minute bugs that showed up at the worst possible time. This checklist help...

Tabular Editor (TE), I have heard this name before. Yes, you probably had it if you work closely with Power BI, then Tabular Editor (TE)is the parallel lead to your PBIX reports. If you haven't explored Tabular Editor (TE), then this blog is for you. With this blog, we will give you all the basic use cases that get ignored in Power BI, but with TE, you can do it seamlessly. There are tons of articles and videos explaining the UI of TE, so we won't be touching it. We will be focusing on different use cases that I normally do with all my Power BI reports. First things first, we will be focusing on the TE version 2 since it's a free tool. You can also opt for version 3, which is a much-improved version than version 2, but I would recommend starting with version 2 and seeing if it suits your needs. Version 3 is a paid version. To download TE Version 2 from this very well known git hub page . Also, do check a small comparison done between the two versions on the TE official webs...

Another week, another blog! This week, we will cover something very basic. If you are a BI developer and work with Power BI, you will be familiar with DAX functions - Values, Value, and Distinct. This blog will cover all the common pitfalls and practical use cases for each of them. Before we start, let's start with a small question. Are distinct and unique means the same? For a very long time, I used to think they were just synonyms, but they aren't. Wait what?? How are they different? Okay, let's understand it. Distinct means each value in a specific column appeared once. In other words, you can say to count all values as 1. If you are a fan of SQL, then you already know that distinct is used to remove duplicates. While unique means you only consider the values that aren't repeated in a column. There's a subtle difference between the 2 that gets ignored easily. Okay, since you are aware of the difference between distinct and unique, we can now start the real acti...

Field parameters are widely used to change fields or measures dynamically in a visualization. If you are new to field parameters, we have covered the basics of field parameters in one of the earlier blogs. Related Read: Mastering Field Parameters in Power BI Field parameters are a powerful way to let users dynamically switch between different fields (like columns or measures) — no drill-down needed. This hands-on guide walks through how to use field parameters to create flexible visuals, build custom slicers, and improve report interactivity. You'll also learn tips on editing parameters, handling implicit vs. explicit measures, and avoiding common mistakes. In this blog, we will take it to the next level. Before we get started, I am using Sample Superstore as my dummy data. So let's get started, and we are first creating a basic field parameter taking all basic measures - Total Sales, Total Quantity, and Profit. We are dragging this field parameter in a basic table visual. Noth...