Pages
1886
Published
2019
The Complete Reference to DAX for Power BI, SQL Server Analysis Services, and Excel
Master every corner of DAX — from basic expressions to advanced calculation patterns — so you can build faster, more accurate data models with confidence.
Marco Russo and Alberto Ferrari are the two practitioners most responsible for teaching DAX to the world, and this book is their complete statement on the language. Covering DAX for Power BI, Analysis Services, and Power Pivot, it moves from first principles through evaluation contexts, filter propagation, time intelligence, and advanced calculation patterns. At 1,886 pages it is a working reference as much as a tutorial — the book professionals reach for when a formula does not behave the way they expect.
DAX looks deceptively simple. A few columns, some functions that resemble Excel, and results that appear almost instantly. Then you write a measure that returns the wrong number and you have no idea why. That gap between "DAX that runs" and "DAX that is correct" is exactly what this book closes.
Marco Russo and Alberto Ferrari have spent years analyzing every corner of the DAX engine, and The Definitive Guide to DAX is the result of that work. It is organized so that a reader who is new to DAX can follow the progression from calculated columns and simple measures through to the evaluation context model that governs everything the language does. It is equally useful as a reference for experienced analysts who need a precise explanation of why a specific pattern behaves the way it does.
The book covers DAX across its three main hosts — Power BI, SQL Server Analysis Services Tabular, and Power Pivot for Excel — so the material applies regardless of which tool you use day to day.
Core topics covered include:
The reference section alone makes this book worth keeping on your desk. Every function entry includes a precise description, argument details, and at least one worked example. When a function has a known gotcha or interacts unexpectedly with filter context, the authors say so plainly.
If you work with data in Power BI or Analysis Services and DAX is part of your job, this is the book that answers the questions that documentation and forum posts cannot fully resolve.
Introduces the DAX language, its data types, operators, and the Tabular data model. You will write your first calculated columns and measures and understand how DAX differs from Excel formulas.
Explains how tables, columns, relationships, and measures fit together in a Tabular data model. You will learn how the model structure shapes every DAX calculation you write.
Covers the table-valued functions that return and filter sets of rows: FILTER, ALL, VALUES, DISTINCT, and related functions. You will use these building blocks in more complex expressions throughout the rest of the book.
Provides a deep, precise explanation of row context and filter context — the two evaluation contexts that govern every DAX expression. You will trace through examples step by step until the behavior of context transition becomes predictable.
Covers the most important function in DAX in full detail, including every filter argument form, context transition, and the ALL family of modifiers. You will learn how CALCULATE reshapes the filter context and why it is central to almost every non-trivial measure.
Explains how to use VAR and RETURN to write cleaner, more debuggable DAX expressions. You will restructure complex nested formulas into readable steps that evaluate correctly and perform well.
Walks through the standard DAX time intelligence functions and explains the calendar table requirements each function relies on. You will build period-to-date, period-over-period, and rolling-period measures for both standard and non-standard fiscal calendars.
Presents complete, production-ready patterns for common business calculations: running totals, market basket analysis, ABC classification, dynamic segmentation, and statistical aggregations. You will adapt each pattern to your own data models.
Examines many-to-many relationships, weak relationships, role-playing dimensions, and the effects of cross-filter direction on DAX results. You will learn when to let the engine handle relationships automatically and when you must control filtering explicitly in DAX.
Introduces DAX query syntax for use in DAX Studio and server-side scenarios, then covers formula engine versus storage engine execution and common optimization techniques. You will measure measure performance and identify the patterns that cause slow queries.
Some familiarity with Power BI or Excel Power Pivot helps, but the book starts from first principles. Readers who have written a handful of measures and want to understand them properly will find the early chapters accessible and the later chapters immediately useful.
The book covers DAX as used in Power BI, SQL Server Analysis Services Tabular, and Power Pivot for Excel. Most examples apply to all three. Where behavior differs between hosts, the authors note it explicitly.
The first half is designed to be read progressively, since each chapter builds on the evaluation context model introduced earlier. The second half, especially the function reference and calculation patterns, is designed for lookup and reference use.
The 2019 edition reflects DAX as it stood at that point. Many core language semantics have not changed, and the evaluation context model is stable. For the newest functions added after 2019, you will want to supplement with the official Microsoft documentation.
The publisher's companion resources for sample PBIX and Excel files are referenced in the book. Check the Microsoft Press product page for the current download location.
If you need a quick-start guide to building Power BI dashboards, this is not that book. It is a detailed technical reference focused on the DAX language itself, not on report design or Power BI service administration.
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