Pages
439
Published
2017
A practical guide to data modeling and DAX patterns for Power BI and Excel Power Pivot
Build analytical data models that answer real business questions, using DAX patterns taught by the field's foremost authorities.
Alberto Ferrari and Marco Russo are the most cited names in the DAX community, and this book shows why. Covering data modeling fundamentals through advanced DAX patterns, it teaches you to think in terms of tables and relationships rather than formulas in cells. Whether you work in Power BI Desktop or Excel Power Pivot, the principles here translate directly into faster, more reliable reports that your stakeholders can actually trust.
Most Power BI and Power Pivot users hit the same wall: the tool is approachable, but the moment a report needs anything beyond a simple SUM or COUNT, progress stalls. The problem is rarely a missing button. It is a missing mental model for how DAX evaluates expressions, how filter context flows through a data model, and why the shape of your tables determines what is even possible to calculate.
Alberto Ferrari and Marco Russo have spent years solving exactly those problems for organizations around the world, and this book distills that experience into a structured, practical curriculum. You start with the fundamentals of tabular data modeling, learning how to design star schemas, choose the right granularity, and decide when a calculated column belongs in the model versus a measure in a report. Every decision is explained in terms of its downstream consequences, not just its immediate syntax.
From there, the book moves into DAX proper. You learn how filter context and row context work, why CALCULATE is the central function of the language, and how to read and reason about the way DAX propagates filters across relationships. These are not surface-level tips. Ferrari and Russo walk through the engine's evaluation logic so that when you encounter an unexpected result, you have the tools to diagnose it rather than guess.
The later chapters cover the patterns that come up repeatedly in real analytical work:
Every pattern is shown in both Power BI Desktop and Excel Power Pivot, so the book serves readers on either platform without feeling like two separate books stitched together. The modeling principles are identical; only the interface details differ, and those differences are called out clearly.
This is not a beginner's click-through tutorial, and it does not pretend to be. If you already know your way around a pivot table and have built at least one basic Power BI report, this book gives you the conceptual foundation and practical patterns you need to build models that hold up under real business complexity.
You learn what a tabular data model is, why the star schema is the standard analytical structure, and how Power BI and Power Pivot store and query data differently from a traditional worksheet.
You write your first DAX measures and calculated columns, learning the syntax rules and understanding when each construct belongs in the model versus the report layer.
You study the two evaluation contexts that govern every DAX expression, trace how filter context flows through relationships, and practice predicting results before running a query.
You learn why CALCULATE is the core of DAX, how it modifies filter context, and how to use its filter arguments and modifiers such as ALL, ALLEXCEPT, and KEEPFILTERS correctly.
You implement year-to-date, quarter-to-date, rolling-period, and period-over-period measures using standard DAX time intelligence functions and custom calendar table patterns.
You model inventory, headcount, and account balance scenarios where values cannot simply be summed across time, using LASTDATE, OPENINGBALANCE, and related patterns.
You handle analytical scenarios that cannot be expressed as simple one-to-many relationships, including shared dimensions, bidirectional filters, and bridging tables.
You build parent-child hierarchies for organizational charts and chart-of-accounts structures using PATH, PATHITEM, and related functions, then expose them as usable report hierarchies.
You implement complex filter and ranking measures that must survive cross-filter interactions and dynamic segmentation requirements common in real business dashboards.
You review modeling and DAX choices through the lens of query performance, learning which patterns are engine-friendly and how to identify slow measures before they reach production.
You should already be comfortable with pivot tables and have built at least one basic Power BI report or Power Pivot workbook. The book explains DAX from its foundations, but it moves at a practitioner's pace rather than a complete beginner's pace.
Both platforms are covered throughout. The underlying modeling principles and DAX language are identical on either platform, and the book notes interface differences where they matter.
The core DAX language and tabular modeling concepts covered here have remained stable. Some UI details in Power BI Desktop have changed, but the evaluation semantics, relationship patterns, and DAX functions taught in the book apply directly to current versions.
The first several chapters build on each other and are best read in order, since filter context and CALCULATE are prerequisites for everything that follows. Later pattern chapters can be used as standalone references once you have that foundation.
Microsoft Press books of this type typically include companion files. Check the publisher's official page for the specific download link, as we do not host third-party publisher assets.
If you have never opened Power BI or Power Pivot and want a step-by-step interface tour, this is not the right starting point. Look for an introductory title first, then return to this book when you are ready to go deeper.
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