Expert Data Modeling with Power BI: Enrich and optimize your data models to get the best out of Power BI for reporting and business needs

I found the first edition of “Expert Data Modeling with Power BI” so valuable I had to buy the second edition when it became available. Even as an experienced Power BI developer I would often bring the book with me to lunch and enjoy reading, highlighting and underlining in it. There were several things I liked about the first edition. First, I liked the fact that the book was written by a consultant that had worked in a variety of situations, and, brought his real-world expertise that he gained to the pages. Second, I liked how thorough the book was, that it covered all aspects of data modeling (data acquisition, data prep, star schema, and advanced data modeling techniques) and was a useful resource for the beginner who could grow into the book, but useful for the experienced dev also. I even found the “Introduction” chapter valuable, but having a good amount of experience when I bought the first edition it was the “Advanced Modeling” techniques that I was most interested in. The second edition, as expected, adds more content, reflecting the many additions to the Power BI product since the first edition. I like the smaller font and the graphic design updates although I liked the first edition graphic design also. The screenshots look better in the second edition and it appears that some screenshots were replaced with actual diagrams to make the content clearer, which I like. I do have a few suggestions for a future revision. In the “Data from Various Sources” section I would love to see one or more examples connecting via an API, perhaps one simple example, and one more complex example. Something else I would find valuable, which the author invariably has run into, is a case study looking at a tangled data model design (bidirectional cross filtering, many to many relationships,…), and then a proposed redesign. In summary, I’m glad I have the second edition of the book and will have to find a willing recipient of my first edition copy that won’t mind my crazy highlighting and underlining.

If you want to build top-quality, high-performing Power BI reports, the make-or-break aspect will be whether you get your data model right. Ever since the first edition of MS MVP Soheil Bakhshi's book came out two years ago, it has been at the top of my list of recommended data modeling books: My only quibble with this book is the title, which might lead you to believe that that it is primarily for expert/advanced users. While the book skillfully addresses advanced topics, it is also the only book I've seen on this topic suitable for beginning Power BI users as well. At over 650 pages, this is an extensive resource that you can grow with as your Power BI knowledge expands over time. Soheil starts with an outstanding introduction to data modeling in Power BI - explaining in clear, concise language with multiple illustrations why the data model is so fundamental to Power BI, and addressing key concepts, such as star schema and denormalization. One of my favorite things about this book is the excellent balance of theory and practice. Soheil does a great job explaining the broader "whys" of data modeling best practices, but also shows you in step-by-step detail the "hows" of implementing these approaches in your own reports - covering the necessary DAX, Power Query and Power BI techniques with excellent clarity. As good as the first edition was, this new second edition is substantially improved, since it addresses in detail the advances in Power BI related to data modeling implemented over the last two years, including: 🔸 Composite Models 🔸 Enabling Direct Query for live connections 🔸 Field Parameters 🔸 Datamarts 🔸 EVALUATEANDLOG for debugging 🔸 The new family of DAX WINDOW functions Whatever your current level of skill with data modeling is, I believe you will find much to learn from in this book.

This book is complex but I have joined the authors group and plan to see what I can learn from the experts.

Brian Julias recommended this book, and even though I've been using the product for years, I still found really good content within. I recommend for architects and anyone who's building semantic models with Power BI.

This book is a great starting point for anyone wanting to learn easy to understand concepts pertaining to data modeling. Some of the high points: Requirements gathering Star Schema DAX, especially time intelligence Calculated columns Creating a Data Table Power Query and most interesting to me personally was the portion devoted to creating a Data Mart. Since this books covers everything from start (modeling) to sharing (Data Mart) this will be a book I will continually reference and would recommend to colleagues.

I have been using Power BI for close to three years on a daily basis and still found several hidden gems in this book. Highly recommend!

Soheil Bakhshi, the author of Expert Data Modeling With Power BI has done what many authors of Power BI books have not and that's by diving deep into the foundations of data modeling, data warehousing and outlining the importance of data structure from the onset of taking on an analysis or visualization project. Bakhshi begins the book with explaining the purpose of the Power BI data platform, but taking it even further when outlining important steps like Getting Data, Transforming Data, Loading the Data, Data Modeling and Data Visualization. He also transitions into detail specifically diving into data preparation, data modeling and data visualization. Novice and less experienced data developers tend to jump right into visualization process without thinking about data structure, performance impact and modeling, but Bakhshi makes the reader understand that the process must be articulated and fully planned out with subject matter experts to ask the import questions of the 5W - 1H; What When Where Who Why and How when laying out table dimensions and facts. He details data modeling designs like the Star Schema and SnowFlaking describing dimension and facts tables and the importance of using PowerQuery and Dax to design special joins, calculated columns and even creating virtual tables in efforts to achieve the star schema which is the goal in presenting a clean and understandable data model before designing a dashboard or report to the report layer. Bakhshi unlocks the steps using a sample database to show the reader how to design and create data models combining fact and dimension tables like sales, geography, customers, time, products and demographics utilizing normalization and de-normalization tables. Bakhshi discusses ETL data loading from SQL, Excel, Text files, Cubes and other sources and the strategies to reduce overhead by limiting the amount of data or keying in on certain scopes of data. In my experience as a BI developer, performance has always been a key issue in report presentation and Bakhshi emphasizes that "an efficient model must perform well, be business driven, decrease the complexity of DAX expressions and have low maintenance costs". To understand some examples using DAX, the reader should have at least a beginner to intermediate knowledge of DAX (Data Analysis eXPressions). Bakhshi provides in great detail a wealth of examples dealing with data types, aggregates, data conversions, primary and foreign keys, Power and Direct Query, DAX, Textual and Explicit measures, virtual tables and models, RLS (Row Level Security), parameters, calculated fields and the like; going into great detail to demonstrate the Power BI tools to achieve any request or desired presentation. I recommend every BI developer purchase this book and work through the examples displayed in it and it will take your PowerBI skills to an expert level. This is a book that you will want by your side or at your fingertips at all times as a reference before and during BI projects. Great work by author, Soheil Bakhshi and by the PackT team!

I strongly believe that data modeling is an essential and vital step when embarking on designing your dashboard. Soheil Bakhshi's book, 'Expert Data Modeling with Power BI,' serves as an exceptionally valuable and hands-on resource for individuals aiming to enhance their proficiency in data modeling within the Power BI ecosystem. Bakhshi, an expert in the field, presents a comprehensive overview of data modeling concepts and techniques, providing clear explanations throughout the book. This book is over 650 pages with 15 chapters divided into 4 sections. Section 1- Data Modeling in Power BI Covers basics of data modeling in Power BI, star schema, snowflaking, Power BI data flows and data marts, use of DAX to create date tables, and using DAX studio Section 2- Data Preparation in Query Editor Covers an introduction to M language and the power query editor, common data preparation steps, and data preparation best practices. Section 3- Data Modeling Covers concepts of data modeling like tables, fields, relationships, and data modeling common best practices Section 4- Advanced Data Modeling It covers advanced techniques like using aggregations, incremental refresh, calculation groups, RLS, OLS, Dataflows, composite models, new features of Power BI like field parameters, and a few new DAX functions like NETWORKDAYS() and a few window functions. One of the book's strengths lies in its focus on Power BI, a popular and powerful tool for data analysis and visualization. Readers are guided through the entire process, from understanding the fundamentals of data modeling to implementing advanced modeling techniques. Bakhshi does an excellent job of bridging the gap between theory and practice by providing step-by-step instructions. This approach allows readers to grasp complex concepts easily and apply them immediately to their projects. Another noteworthy aspect of this book is its attention to best practices and optimization strategies. Bakhshi provides valuable insights on data modeling considerations, performance optimization, and data integrity, ensuring that readers develop a solid foundation for building efficient and reliable data models. My favorite sections in the book: 1. Time intelligence and data modeling 2. 15 Common data preparation steps 3. Query folding and its impact on data refresh 4. Data modeling common best practices 5. Using Calculation Groups 6. New DAX functions