Pages
712
Published
2022
A practical guide to Power BI data modeling, DAX, and enterprise-grade report design
Go from connecting raw data to publishing polished, high-performance Power BI reports your stakeholders will actually use.
Mastering Microsoft Power BI by Greg Deckler, Brett Powell, and Leon Gordon is a 712-page practical guide for analysts and developers who already know the basics and want to work at a professional level. The book covers the full Power BI workflow: data ingestion, Power Query transformations, data modeling, DAX measures, report and dashboard design, and deployment to the Power BI service. Each chapter builds on real scenarios so you finish with skills you can apply on Monday morning.
Power BI is easy to start with. It is hard to do well. Dragging fields onto a canvas gets you a chart, but it does not get you a report that loads in two seconds, scales to millions of rows, or answers the question a CFO is actually asking. That gap between "I made a bar chart" and "I built something production-ready" is exactly what this book closes.
Mastering Microsoft Power BI is written by three practitioners who have built real solutions for real organizations. Greg Deckler, Brett Powell, and Leon Gordon bring complementary expertise across DAX authoring, data architecture, and enterprise deployment. The result is a book that does not waste pages on introductory content you already know. It starts where most tutorials stop.
The first part of the book works through data ingestion and Power Query. You will learn to connect to a wide range of sources, shape data efficiently, and avoid the transformation mistakes that cripple performance downstream. The authors explain how Power Query works under the hood so you can diagnose problems instead of guessing at solutions.
Data modeling gets a full treatment. You will build star schemas, manage relationships, and understand why the model you design dictates what DAX you can write. Poor models produce slow, brittle reports. The book shows you what good looks like and how to get there from messy source data.
DAX is the heart of Power BI analytics, and it receives the most detailed coverage in the book. You will work through calculated columns, measures, and the evaluation context model that determines how every DAX expression behaves. Time intelligence, ranking, segmentation, and advanced filter manipulation are all covered with worked examples you can adapt to your own data.
Report and dashboard design chapters address layout, visual selection, formatting, and the design decisions that determine whether a report communicates clearly or generates support tickets. Deployment and administration chapters cover the Power BI service, workspaces, row-level security, scheduled refresh, and the governance questions that arise when you roll out Power BI across a team or organization.
At 712 pages this is a substantial reference. You can read it cover to cover or treat it as the book you reach for when a project demands something you have not done before. Either way, it is aimed squarely at the analyst or developer who wants to stop guessing and start building with confidence.
Set up connections to the most common data sources Power BI supports, from flat files and databases to cloud services. Learn which connector type to choose and how source settings affect downstream refresh.
Use Power Query to clean, reshape, and merge data before it reaches the model. Understand how the M language works so you can edit queries directly instead of relying solely on the GUI.
Build a proper star schema with fact tables, dimension tables, and correctly configured relationships. Understand cardinality, cross-filter direction, and why model design determines everything that follows.
Write your first calculated columns and measures and learn why the distinction matters. Work through the row context and filter context model that governs how every DAX expression evaluates.
Apply CALCULATE, FILTER, and context transition to solve real analytical problems including ranking, cumulative totals, and dynamic segmentation. Build measures that behave correctly regardless of how a user slices the report.
Implement year-to-date, prior period, moving average, and other time comparisons using DAX time intelligence functions. Configure a date table that supports both standard and custom fiscal calendars.
Select the right visual for each analytical question and apply layout and formatting decisions that improve clarity. Learn which visual choices reduce cognitive load and which ones generate confusion.
Profile slow reports using Performance Analyzer and DAX Studio to isolate whether the problem is in the model, a query, or a visual. Apply targeted fixes rather than guessing at solutions.
Design and test role-based row-level security to restrict data access by user or group. Extend the patterns to multi-tenant scenarios where a single report must serve different organizations.
Publish reports to workspaces, configure scheduled data refresh, and manage deployment pipelines for development, test, and production environments. Understand the governance and licensing decisions that arise at the organizational level.
You should already know how to navigate the Power BI Desktop interface, load at least one data source, and create a basic report. The book does not cover introductory concepts and moves quickly into intermediate and advanced territory.
The book was published in June 2022 and covers the Power BI release current at that time. Power BI updates frequently, so a small number of UI details may differ, but the data modeling and DAX content remains fully applicable.
The book introduces DAX from the ground up within the context of Power BI data modeling, so prior DAX experience is not required. Familiarity with Excel formulas or SQL will help you move through the earlier DAX chapters faster.
Packt titles typically include downloadable code and data files via the publisher's website. Check the book's product page on Packt's site for access instructions after purchase.
The structure supports both approaches. You can read it sequentially to build a complete picture, or navigate directly to chapters on DAX patterns, security, or deployment when a specific project demands it.
The primary focus is Power BI Desktop and the Power BI service. Power BI Report Server is not a central topic, so readers working exclusively in on-premises environments may find some deployment chapters less directly applicable.
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