Microsoft Power BI Cookbook: Convert raw data into business insights with updated techniques, use cases, and best practices 3rd ed. Edition

Not recommended for beginners... But it is a great book!Color Images are are a great complement!

First off - this is not a book for beginners. I would characterize it as an intermediate to advanced level book. If you are just starting with Power BI, go with "Learn Power BI, 2nd edition", also by Greg Deckler.Here are three reasons why I like this book so much and recommend it so highly:🔸 It's a CookbookThese are my favorite type of data books, since they are an incredibly efficient way to learn.This book is divided into ≈100 different "recipes" - very specific instructions on how to do one particular thing (e.g., Extending the Core M Library, Configuring On-Premises Data Connections, etc.). This makes it really easy to separate the things you already know from the areas in which to focus your learning.🔸 It's a "Learn by Doing" BookThe way I learn best is "tell me, show me, let me do it myself", and this is the paradigm the book is built around. Each recipe starts with a brief intro and then a section called "Getting Ready". The authors have prepared an extensive repository of over 100 PBIX files that enable you to work through the techiques on your own with little to no setup, and then check your work.🔸 It's a Greg Deckler BookGreg is one of the most knowledgeable and innovative thinkers in the global Power BI commmunity, so you can be certain you're not going to get a rehash of the standard topics and approaches.A great example of this is the chapter entitled "Parameterizing Power BI Solutions" which consists of six detailed recipes for employing powerful parameterization techniques across hashtag#Mcode and hashtag#DAX in an integrated way to develop custom analytical solutions in your reports. Not something often discussed, but incredibly useful.Similarly, the book also includes a 30 page, 5 recipe chapter called "Getting Serious About Date Intelligence", which is the most detailed writeup I've seen to date on what I refer to as the "offset" approach - just a decisively better way to do traditional "time intelligence" calculations - simpler, more flexible, more reliable, and more performant.One other thing - this book looks **great**. It's full of hi-res color screen shots and laid out in a really intuitive and attractive way.I could go on and on, but this is just a phenomenally well-implemented book that any serious Power BI user will benefit greatly from having in their collection.

After having gone through building a PowerBI dashboard from scratch for my org, here’re my personal takeaways from the book:🚀 Early on in Ch 3, the book emphasizes on Design Decisions such as efficient semantic models using techniques like star schemas and DirectQuery storage modes. For AI practitioners working with large datasets, these optimizations ensure models remain performant while supporting complex machine learning pipelines.🧮 Ch 6 introduces “Hybrid tables”, which combine real-time and historical data in a single model. A practical example demonstrates hybrid tables to deliver near-instant analytics for scenarios such as monitoring live IoT data streams while maintaining historical trends, which can be quite useful for building dynamic, low-latency dashboards.🛠️ Ch 8 explores parameterization in Power BI, where a coding example walks through setting up "What-If" scenarios using parameter tables for predictive modeling or scenario analysis in AI projects.🔗 A top highlight of this book is Ch 13 on integrating Power BI with Microsoft Fabric, showcasing Fabric's data engineering and analytics capabilities alongside Power BI's visualization strengths. For AI practitioners, this opens up possibilities for seamless workflows: ingesting raw data into Fabric's data lake, transforming it with Spark or Python notebooks, and visualizing insights in Power BI dashboards. Early-career professionals aiming to work with enterprise-grade data platforms will find this particularly valuable.📉 While this book unfortunately does not discuss Preview features such as the TMDL format and PBIP project files (which from my direct experience can be crucial for Source Control and CI/CD), I presume that’s okay, just because the features are marked as Preview and hence the official Microsoft Learn documentation may really be the source of truth for latest updates.For most PowerBI developers, I would _not_ recommend this book because of the sheer density of the content, where they’d likely be better-off asking their specific question to a search-based LLM or just watching a relevant YouTube tutorial (eg: there’re *dedicated* videos just on Date Pickers and design decisions around them!). This book is really best suited for Data Engineers or Practitioners who have to work with PBI as a major part of their job to really have a refined, holistic understanding of PBI’s workings.

This Book covers a wide range of helpful “Recipes” ranging from Setting up Power BI (Installation and Licensing), ETL (Extract, Transform, and Load), Building a Data Warehouse, Optimization, Reporting, Governance, etc. Once again Packt managed to find Subject Matter Experts who were able to provide a wealth of knowledge in a clear manner and I wish I would've had this Book a few years ago.

I'll be clear and brief: this is a great Power BI cookbook! I've read a handful of Power BI books over the years and I think this is one of the best ones to date. It covers everything from licensing to getting started with Microsoft fabric. With more than 550 pages across 13 chapters, you will walk away with a deep understanding of Power BI best practices. Easy to read, follow, and understand too!