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Data Modeling With Power Bi Guide - Expert Techniques

by The BI Expert Collective

Reference 2023 450 pages
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About This Book

This essential technical guide dives deep into the architectural principles and best practices required for creating robust, scalable data models within Microsoft Power BI. Learn the crucial steps for transforming complex raw data sources into high-performance, analytical structures. It is mandatory reading for professionals moving beyond basic report generation.

What You'll Learn

  • Mastering the intricacies of the DAX language for complex calculations and time intelligence.
  • Implementing Dimensional Modeling (Star Schema) and understanding relationship cardinality.
  • Techniques for optimizing data refresh rates and report performance across massive datasets.

About the Author

The BI Expert Collective is comprised of certified Microsoft Data Platform MVPs and seasoned consultants, bringing decades of experience in enterprise data architecture and proven business intelligence implementation. Their collective expertise ensures practical, reliable, and industry-leading advice grounded in real-world scenarios.

Who Should Read This

Data analysts, BI developers, data engineers, and Power BI users who need to build professional-grade, high-performance analytical models and reports.

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Frequently Asked Questions

Is this book suitable for beginners in Power BI?

While it introduces foundational concepts, this book focuses heavily on intermediate to advanced modeling techniques and assumes familiarity with the basic Power BI interface.

What is the primary focus of the data modeling techniques covered?

The primary focus is on dimensional modeling, optimizing table relationships, and ensuring high performance using the VertiPaq engine.

Does this guide cover the DAX language?

Yes, a significant portion is dedicated to mastering advanced DAX functions specifically for creating measures and calculated columns within optimized models.

Why is proper data modeling important in Power BI?

Proper data modeling is critical because it directly impacts report performance, data accuracy, maintainability, and user experience for large-scale business intelligence solutions.

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CategoryReference
LanguageEnglish
Last UpdatedApril 2026