Direct Lake on OneLake hit GA this month. The two flavours, the security shift you can't roll back, and a safe audit-validate-migrate workflow with semantic-link-labs.

Every Fabric project I've worked on, every single one, has had questions around SKU sizing, capacity, capacity metrics, monitoring, and utilisation. The list goes on. I've been working with Power BI since its early days, and I've been in the BI world for many years before that. In all that time, I don't think I've come across a single product or project where it's easy to say "this is the right size." There's never really a right or wrong answer. I sometimes wonder if that's

A single Python file that creates complete monitoring infrastructure for Microsoft Fabric: lakehouse, tables, semantic model with relationships and DAX measures. Deploy in 5 minutes and start tracking your ETL pipelines immediately.

It's one of those blog posts I write for my own reference, and I suspect many of you will find it useful too. If you're working with Semantic Link and Semantic Link Labs in Microsoft Fabric, you've probably hit that moment where something doesn't work, and you realise your library version is out of date. Fabric pre-installs semantic-link, but the version bundled with your runtime isn't always the latest. And semantic-link-labs? That one you need to install yourself. I got tir

If you prefer to watch, I have recorded a video. - https://youtu.be/70WYukFGvt0 A year ago, I started my solopreneur journey and did what any sensible millennial would do: I created a shiny new website at data-nova.io . But there was a problem. I'd been blogging on my old site, prathy.com , for years, and there was content there I genuinely cared about. I wanted everything in one place. Wix had this handy little tool that promised to seamlessly import all my WordPress blogs.

Building AI agents to create Power BI reports taught me something crucial: functional doesn't mean usable. My agent kept cramming everything onto one screen because it didn't understand design intent. This post explores visual cues and the principles that make dashboards intuitive, not just technically correct.

You are not alone! I recently completed some work for a client regarding orphaned deployment pipelines. In small teams, where one or two developers handle most of the tasks, certain items may become orphaned, and accessing them can be challenging. While using REST API to achieve many things is common, working with PowerShell has never been my strong suit. Fortunately, this can be accomplished quite easily with Fabric and Fabric Notebooks. Below is a quick code snippet you can

SemPy offers many possibilities with Semantic Models in Microsoft Fabric, some of which are remarkably effective and simplify some tedious tasks. As Data Analytics Developers, we often debate the best naming conventions. However, business users expect us to set aside our fixation on naming conventions and create more readable outputs with a simple design. When we create our models for Power Users, Self-Service BI users, or Power BI designers, they need simple, explainable nam

Quick guide to convert Power BI Direct Lake models to Import mode and rebind reports using Semantic Link Labs. Perfect for publishing open d

Copying Power BI reports or notebooks across Fabric workspaces isn’t exactly smooth — especially if you want to move things in bulk. In this blog, I walk through how I used the Fabric CLI inside a notebook to automate this task. No external tooling, no manual fiddling. Just a smart little hack with: • Environment-based authentication • Folder ID lookups (with auto-create if missing) • Safe copy logic with fab cp • Final clean-up with a folder PATCH

Cloning a semantic model or report in Power BI isn’t always recommended—but sometimes, it’s the smartest move. Whether you’re juggling multiple environments or building templates for different domains, this step-by-step guide shows how to clone semantic models and reports with Python using sempy_labs, and rebind them with ease.

In my last post, I discussed how I've been using Sempy and SemPy Labs to convert column names to Snake Case . This post will explore the next important step: creating and managing measures. Having all measures simplifies processes significantly; it makes changes easier, makes smoother documentation, enhances AI productivity and facilitates deployment to a new semantic model. What I appreciate most is the ability to add descriptions and organise measures into folders effortles

Naming conventions are a small but crucial part of creating effective data solutions. In this post, I explore how to do in Microsoft Fabric

It’s one of those blog posts I write for my own reference as I often find myself needing this code. I…

Understanding the relationships between datasets is crucial in data analytics, especially in the world of self-service BI. Sempy, a Python library unique…

Documentation is a critical and tedious part of every project. However, it is essential to review existing developments or document new…

Can you believe how amazing and hectic March has been?! So many community members got to experience some major conferences all…

Like many I am also playing with Fabric, many of my clients are also excited about Fabric and want to know…

If you are a consultant like me, you know how hard it can be to access Power BI Admin API or…

I had been following the hints and clues on Twitter, where some Power BI team members were changing their job titles…