Architecting Power BI Solutions in Microsoft Fabric E-Book

Nagaraj Venkatesan

• Herausgeber: Packt Publishing
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 484

Veröffentlichungsjahr: 2025

Beschreibung

Business Intelligence (BI) tools like Power BI are used by a wide range of professionals, creating diverse and complex scenarios, and finding the right solution can be daunting, especially when multiple approaches exist for a single use case. The author distills his 17 years of experience on various data platform technologies in this book to walk you through various Power BI usage scenarios.
The book is structured around Power BI usage scenarios, such as developing solutions for corporate BI reporting, self-service BI reporting, and Power BI for data scientists and independent software vendors (ISVs). Each part highlights common data issues encountered in the usage scenario, the correct approach to solve the problems, and supporting technical guidance. The chapters also introduce you to some of the latest enhancements in Power BI, such as Microsoft Fabric integration with Power BI, AI features like Copilot, Power BI Git integration, and Power BI Governance features.
By the end of this book, you’ll have learned how to design optimal solutions using Power BI components and pick the right tool for the job, while adhering to security and performance best practices.

Leseprobe

Architecting Power BI Solutions in Microsoft Fabric

Design optimal solutions using Power BI to address common data problems

Nagaraj Venkatesan

Architecting Power BI Solutions in Microsoft Fabric

Copyright © 2025 Packt Publishing

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First published: April 2025

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“Who am I? - Wisdom’s lessons what are they

that fill my mind? - and me who’d know

Had not the Lord of heaven made me His own?” – Manikkavasagar

Dedicated to the holy feet of Lord Shiva

Contributors

About the author

Nagaraj Venkatesan is a cloud solution architect working for Microsoft. Nagaraj has nearly two decades of experience in the data and AI domains. Nagaraj works with customers across the globe, solving complex data and analytics problems, helping them achieve their objectives. Nagaraj is also passionate about sharing the tricks of the trade with the community, which led him to write his first book, on Azure Data Engineering, in 2022. Nagaraj has been a regular speaker at technical conferences, community events, and user group meetups since 2015. Acknowledging Nagaraj’s contribution to the community, Microsoft awarded him the Most Valuable Professional (MVP) award for the years 2016 and 2017.

First, I would like to thank almighty Lord Shiva for giving me the strength to write the book, Architecting Power BI Solutions in Microsoft Fabric, which took 18 months to complete. I would like to thank my parents and my friends for encouraging me during all the challenging times in this period. I would like to thank my wife and son for sticking with me throughout this journey. Special thanks to Packt’s publishing team for all the support.

About the reviewers

Ankit Kukreja is a seasoned professional with over 8 years of experience in data analytics and business intelligence. Specializing in Power BI solutions, workflow automation, and data optimization, Ankit has consistently delivered impactful results across industries. As a Power BI superuser, he actively contributes to the platform and engages with peers to foster learning and collaboration. With advanced certifications in Power BI, Power Platform, and Azure, his technical proficiency stands out. He also contributed as a reviewer for The Complete Power BI Interview Guide.

Ankit would like to thank his son, wife, and family for their unwavering support throughout his career.

Ananya Ghosh Chowdhury, a leader in data and AI at Microsoft, helps organizations leverage AI and advanced analytics to drive transformative strategies and impactful business outcomes. As a senior cloud solution architect, she specializes in crafting enterprise-grade solutions powered by AI, machine learning, and analytics.

With prior experience at Amazon, CVSHealth, PwC, and Cognizant, she has deep expertise in engineering and data science. An author, mentor at Microsoft for start-ups, advisor to AI-focused start-ups, responsible AI advocate, and sought-after speaker in industry conferences, Ananya also serves on the AI Xecutive Council and the Harvard Business Review Advisory Council, and many others, showcasing her thought leadership in the field.

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Table of Contents

Preface

Part 1: Power BI Fundamentals

1

Decoding Power BI

Technical requirements

Power BI overview

Power BI Desktop

Connecting to the data source

Transforming data and building a semantic model

Enhancing a semantic model

Adding visualizations

The Power BI service

Accessing the Power BI service

Collaboration in the Power BI service

Creating dashboards

Tenant administration

Power BI dataflows

Advantages of dataflows

Other Power BI components

Power BI Gateway

Power BI paginated reports

Power BI Report Server

Power BI goals/scorecards

Real-time datasets

Summary

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2

Power BI Licensing

Technical requirements

The Power BI free license

Power BI Desktop

Publishing to the Power BI service using a free license

The Power BI Pro license

Fabric capacity

Capabilities of F64 SKUs and above

Power BI Premium per user

Power BI Premium per capacity

Licensing for Power BI Embedded applications

Fabric F-SKUs for embedding scenarios

Power BI EM SKUs

Power BI Premium P SKUs

Power BI A SKUs

Power BI SKU resource allocation comparison

Power BI Report Server licensing

The Power BI licensing decision tree

Summary

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3

Understanding Collaboration and Distribution in Power BI

Technical requirements

Introducing Power BI Workspace

Exploring roles and permissions in Power BI Workspaces

Sharing reports and semantic models

Semantic model sharing

Report sharing

Publishing apps and reports

Staged publishing using Workspaces and Apps

Restricting direct access to Workspaces

Sharing via app, Workspace role, or granular permission

Scenarios for sharing via App

Sharing via Workspace role

Sharing via granular permission

Summary

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4

Power BI Usage Patterns

Technical requirements

Introduction to Power BI usage patterns

Enterprise BI usage pattern

Semantic model development

Report development

Publishing and report distribution

Self-service BI usage pattern

Managed self-service BI pattern

Summary

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Part 2: Designing Enterprise BI Solutions

5

Deciding on the Storage Mode

Technical requirements

Choosing the storage mode

High performance required

Need the latest data?

Data residency or security requirements

A semantic model exists and it is in Import mode

Does the model fit into the memory?

Selective tables with high performance acceptable?

Understanding composite models

Exploring aggregations

Workspace license mode is PPU or dedicated capacity only

Manual aggregation

Automatic aggregations

Choosing the storage mode – continued

Is the data required in a semantic model?

Data is available in a semantic model but needs to be combined with other data sources

Summary

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6

Deciding on an Intermediate Data Store

Technical requirements

Introducing dataflows

Creating a dataflow

Using a dataflow with a user-managed Azure Data Lake account

Sample scenario

Introducing datamarts

Default semantic model

Comparing dataflows and datamarts

Availability

Performance

Security

Using a decision tree to decide between a dataflow and a datamart

Summary

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7

Understanding Microsoft Fabric

Technical requirements

An overview of Fabric

Challenges in traditional analytics solutions

Components of Fabric

Reviewing the Fabric architecture

OneLake storage

Compute via Fabric capacities

Exploring Lakehouse and Data Warehouse

Lakehouse overview

Data Warehouse overview

Features of lakehouse and data warehouse

Comparing lakehouses, warehouses, dataflows, and datamarts

Summary

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8

Managing Semantic Model Refresh

Technical requirements

Performing full semantic model refresh

Scheduling data refresh in the Power BI service

Performing manual data refresh in the Power BI service

Performing refresh using REST application programming interface (API) calls

Performing refresh using a data engineering pipeline (Data Factory)

Performing refresh using an XMLA endpoint

Performing incremental refresh

How incremental refresh works

Exploring advanced refresh techniques

XMLA endpoint refresh

REST API refresh

Enhanced refresh using the REST API

Refreshing from Fabric notebook

Using a decision tree to decide the semantic model refresh method

Summary

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9

Performing Optimizations in Power BI

Technical requirements

Optimizing a semantic model

Understanding data storage in a semantic model

Semantic model optimization best practices

Semantic model optimization using VertiPaq Analyzer

Using Tabular Editor’s Best Practice Analyzer to optimize semantic models

Optimizing semantic model refresh

Removing unwanted columns

Removing unwanted tables

Ensuring query folding

Performing streaming operations first

Performing joins operations at the source

Pushing calculated columns to the source

Selecting between calculated columns and measures

Picking privacy levels

Picking the right connector

Selecting the semantic model storage mode

Using advanced semantic model refresh techniques

Using tools to troubleshoot semantic model refresh performance

Performing report optimizations

Visuals optimization

DAX optimization

Summary

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10

Managing Semantic Model Security

Technical requirements

Understanding Power BI architecture and data storage

Data residency

Data residency in dedicated capacities (Fabric capacities, Power BI P SKUs, EM SKUs, and A SKUs)

Designing data security

Configuring encryption at rest

Configuring object-level security

Implementing row-level security

Steps to configure row-level security

Summary

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11

Performing Power BI Deployments

Technical requirements

Certifying Power BI artifacts

Endorsement badges

Applying endorsement badges

Understanding deployment pipelines

Using deployment pipelines

Deployment process using deployment pipelines

Managing Power BI Git integrations

How to configure Git integration

Understanding the advantages of Git Integration

Summary

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Part 3: Power BI for Business Users

12

Leveraging Artificial Intelligence in Power BI

Technical requirements

Exploring data using AI

Quick insights

The Analyze feature

The decomposition tree

Leveraging Copilot in Power BI

Leveraging Copilot in Power BI for business users

Leveraging Copilot in Power BI for technical users

Leveraging AI in self-service BI scenarios

Summary

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13

Integrating Power BI with Microsoft 365 Tools

Technical requirements

Exploring Power BI semantic models using Excel

Other methods to connect to Excel from Power BI

Experiencing Power BI with Microsoft PowerPoint

Collaborating on Microsoft Teams with Power BI apps

Adding a Power BI report to a Microsoft Teams meeting

Adding the Power BI app to a Microsoft Teams channel

Summary

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Part 4: Power BI for Data Scientists

14

Uncovering Features of Power BI for Data Scientists

Technical requirements

Decoding the data science process

Defining problem statement

Data discovery and exploration

Experiment

Operationalize model

Visualizing insights

Understanding Fabric’s data science architecture

Developing machine learning model using AutoML

Understanding Fabric semantic link

Using semantic link with pandas

Connecting to a semantic model using Apache Spark

Exploring visualization features for data scientists

Performing clustering

Detecting anomalies

Visualizing R/Python scripts

Exploring Power BI integration with AI Insights

Performing sentiment analysis

Summary

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Part 5: Power BI for Administrators

15

Protecting Data Using Microsoft Purview and Defender

Technical requirements

Protecting data using sensitivity labels

Configuring sensitivity labels

Sensitivity label inheritance

Inheritance via data source

Configuring Microsoft Defender for Cloud Apps for Power BI

Preventing data leaks using data loss prevention policies

Controlling access using protection policies

Securing Power BI using Conditional Access policies

Summary

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16

Designing Power BI Governance

Technical requirements

Understanding the key responsibilities in Power BI

Semantic model development

Report development

Workspace administration

Certifying artifacts

Performing deployments

Capacity administration

Domain administration

Power BI administration

Unpacking designing a governance model

Designing Power BI governance model for enterprise BI

Designing Power BI governance model for managed self-service BI

Designing Power BI governance model for self-service BI

Company business health workspace

Marketing lead insights workspace

Campaign for ABC workspace

Summary

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17

Managing Fabric Capacities

Technical requirements

Understanding Fabric capacities

Background and interactive operations

Calculating capacity utilization

Demystifying the concepts of bursting, smoothing, and throttling

Monitoring Fabric capacities

Managing capacities

Query Memory Limit

Query Timeout

Max Offline Dataset Size (GB)

XMLA endpoint

Devising capacity management strategies

Scaling up the capacity

Splitting the capacity

Procuring new capacity

Backup capacity

Summary

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Index

Other Books You May Enjoy

Preface

Microsoft Fabric is Microsoft’s modern data and analytics platform that offers several services for data engineering, data science, real-time data streaming, data visualization, and so on. Power BI in Microsoft Fabric is a data visualization service and the most popular tool for visualizing data. The simplicity with which the tool has been designed means anyone with near-zero coding skills can build reports, publish them to share with others, and gain insights out of data. Easy adoption, however, is a double-edged sword. While the advantage of the quick adoption of Power BI is that everyone gets access to data, it also means you need to ensure that the data is used in Power BI in a performant, secure, and optimal way, as there will be more users of the data. Improper use of data in Power BI could result in data leaks, reports being too slow to be usable, or incorrect data being shown across reports.

So, this book helps you to design and develop high-quality solutions using Power BI. Whether you are an expert in Power BI or a novice, this book will help you design Power BI solutions. This book is not about every feature of Power BI, explaining how it works or how to develop reports. It is about making the right technical decisions when building solutions.

I have worked with some of the largest companies in the world, who have built incredible solutions using Power BI. The biggest challenge most companies face is deciding when to use which feature of Power BI. While Microsoft’s official documentation is fantastic and explains each feature in detail, there is a gap when you need to compare features and identify which feature is most suitable for a scenario. So, in this book, I have taken some of the most common scenarios where customers generally face difficulties in making technical decisions and offered in-depth guidance so that you can build high-quality solutions. Please do note that while this book is based on my customer experiences, none of it represents my employer’s opinion and the book is written in a personal capacity.

The book is organized into multiple parts, with each part comprising a group of chapters. The first part covers Power BI fundamentals, so even if you have had no exposure to Power BI and are tasked with building a solution, you could still follow the book. After the fundamentals, the book moves on to cover enterprise Business Intelligence (BI) solutions, with a focus on building high-quality solutions that are to be used across the organization. After the enterprise BI solutions part, we focus on the features of Power BI for business users, which will cover AI features of Power BI and Microsoft 365 integration features of Power BI. We also have a part for data scientists using Power BI. Finally, there is a part that focuses on key topics of interest for administrators, such as data security, governance, and platform management.

As Power BI is integrated with Microsoft Fabric, this book will also focus on features of Microsoft Fabric such as data engineering pipelines, Dataflow Gen2, data science notebooks, data warehouses, and lakehouses wherever appropriate.

Who this book is for

Architects looking to create data and analytics solutions using Power BI would find the book very useful, irrespective of their exposure level to Power BI. Power BI developers and data engineers looking to develop Power BI solutions will learn best practices to be followed while building solutions in Power BI. Power BI Administrators will also learn how to optimize, govern, and secure the Power BI environment.

What this book covers

Chapter 1, Decoding Power BI, is an introductory chapter on Power BI. The chapter introduces Power BI Desktop, connecting to a data source, building a report/dataset/dashboard, and publishing reports and datasets to the Power BI service. The chapter serves as a warmup for the rest of the book.

Chapter 2, Power BI Licensing, covers, in detail, the various licensing options available in Power BI, namely, the free license, Power BI Pro, Premium Per User, Fabric Capacity SKUs, Power BI Premium, and Power BI Embedded.

Chapter 3, Understanding Collaboration and Distribution in Power BI, covers various roles and permissions available within Power BI and how they can be used to distribute content effectively.

Chapter 4, Power BI Usage Patterns, introduces various scenarios or usage patterns in Power BI, such as enterprise BI, self-service BI, and managed self-service BI solutions. The book is structured into many parts, with each part corresponding to a Power BI usage pattern, and the chapter lays the foundation for the rest of the book.

Chapter 5, Deciding on the Storage Mode, compares the various data connectivity modes available in Power BI, such as import mode, DirectQuery mode, live connections, and composite models, and offers in-depth guidance on when to pick which option.

Chapter 6, Deciding on an Intermediate Data Store, introduces the two popular intermediate data stores in Power BI, namely, dataflows and datamarts. The chapter compares the various features of dataflows and datamarts and offers detailed guidance on picking the right choice between the two.

Chapter 7, Understanding Microsoft Fabric, introduces Fabric architecture and the various components of Fabric, such as OneLake storage, lakehouse, and warehouse. The chapter explains the advantages of Direct Lake connectivity mode and teaches how to use it. The chapter offers a detailed comparison of datamart, dataflow, lakehouse, and warehouse capabilities and provides guidance on selecting one over another.

Chapter 8, Managing Semantic Model Refresh, covers the various techniques available to refresh semantic models, such as refreshing from the Power BI service, using REST APIs, XMLA endpoints, and Fabric data engineering pipelines. The chapter compares the advantages and disadvantages of all the semantic model refresh techniques.

Chapter 9, Performing Optimizations in Power BI, covers in-depth optimization techniques across three major topics, namely, optimizing the semantic model, optimizing semantic model refresh, and performing report optimizations. We will cover best practices when designing a semantic model, VertiPaq engine internals, and the usage of tools such as Tabular Editor for optimization. We will also cover Power Query optimization methods, as well as best practices in designing performant reports and the usage of tools such as Performance Analyzer and DAX Studio for report optimization.

Chapter 10, Managing Semantic Model Security, covers the Power BI security architecture, explaining how data is stored inside Power BI. The chapter also covers key security features of Power BI, such as data encryption, row-level security, and object-level security.

Chapter 11, Performing Power BI Deployments, covers the semantic model, report certification, and the publishing/release management process. It covers the usage of deployment pipelines for moving Power BI artifacts across environments such as development, test, and production. The chapter also provides an overview of Git integration with Power BI, explaining its benefits in operations such as the version control of Power BI artifacts, and the Continuous Integration and Continuous Deployment (CI/CD) process for Power BI artifacts.

Chapter 12, Leveraging Artificial Intelligence in Power BI, covers how Artificial Intelligence (AI) can be used by technical and non-technical users inside Power BI. The chapter covers how to use Copilot within Power BI effectively and also covers other AI features useful for data exploration, such as quick insights, the decomposition tree, and smart narratives.

Chapter 13, Integrating Power BI with Microsoft 365 Tools, covers how business users can use familiar tools such as Microsoft Excel, Word, PowerPoint, and Teams with Power BI and be productive.

Chapter 14, Uncovering Features of Power BI for Data Scientists, introduces the data science process and covers the features of Fabric/Power BI for data scientists’ use, such as AutoML and Fabric semantic links. The chapter also covers useful AI features for data scientists, such as automatic clustering, anomaly detection, and sentiment analysis of text using AI insights.

Chapter 15, Protecting Data Using Microsoft Purview and Defender, focuses on security features and solutions in Power BI that prevent data leaks, external attacks, and unintended data sharing. This chapter focuses on designing security solutions using Microsoft Purview sensitivity labels, Microsoft Purview data loss prevention policies, and Microsoft Defender for Cloud Apps security for Power BI.

Chapter 16, Designing Power BI Governance, focuses on the various usage scenarios involved in Power BI implementation, the roles or personas involved, their responsibilities, and the permissions to be granted to each persona. This chapter will provide guidance on designing a governance model for various usage scenarios, such as enterprise BI, self-service BI, and managed self-service BI.

Chapter 17, Managing Fabric Capacities, helps you understand Fabric capacity administration fundamentals such as how capacity units are measured, what background and interactive operations are, and how capacity utilization is calculated. The chapter also explains the concepts of bursting, smoothening, and overages in Fabric capacity. The chapter offers a few capacity management strategies to manage capacities that are throttled due to resource utilization spikes.

To get the most out of this book

Software/hardware covered in the book

Operating system requirements

Power BI Desktop

Windows

Microsoft Office

DAX Studio

Tabular Editor

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Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter/X handles. Here is an example: “Mount the downloaded WebStorm-10*.dmg disk image file as another disk in your system.”

A block of code is set as follows:

html, body, #map { height: 100%; margin: 0; padding: 0 }

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “Select System info from the Administration panel.”

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Part 1: Power BI Fundamentals

This part of the book lays the foundation for the rest of the topics covered in the book. It focuses on introducing the basics of Power BI, so that even readers who have minimum or no exposure to Power BI are able to follow the book. Even if you are an experienced Power BI practitioner, it is recommended to go through these chapters as the concepts explained will be referenced in the rest of the book.

This part has the following chapters:

Chapter 1, Decoding Power BIChapter 2, Power BI LicensingChapter 3, Understanding Collaboration and Distribution in Power BIChapter 4, Power BI Usage Patterns

2

Power BI Licensing

One of the important subjects to understand while learning the basics of Power BI is Power BI licensing. Power BI licenses hugely influence product capabilities, and hence, you need to have a thorough understanding of Power BI licensing to build effective solutions. In this chapter, we will introduce you to all the Power BI license options available, allowing you to understand the differences in the product capabilities of each license/Stock-Keeping Unit (SKU) level. We will also include a decision tree in this chapter, helping you to decide on an appropriate license for each scenario.

The topics covered in this chapter are as follows:

The Power BI free licenseThe Power BI Pro licenseFabric capacityPower BI Premium per userPower BI Premium per capacityLicensing for Power BI Embedded applicationsPower BI Report Server licensingThe Power BI licensing decision tree

By the end of the chapter, you will have a good understanding of Power BI licensing options and have the knowledge to decide when to pick which license.

Technical requirements

The technical requirements for this chapter are as follows:

A work or school account with access to www.powerbi.comPower BI Desktop

The Power BI free license

Can you do anything for free in Power BI? The answer is a big yes! Here are the things you can do for free in Power BI:

Create reports using Power BI DesktopPublish reports to My workspace in the Power BI service

Let’s look at each of these items in greater detail in the following sections.

Power BI Desktop

As introduced in Chapter 1, Power BI Desktop is a free report-authoring client tool. You can download and install the tool, connect to a data source, and build reports for free. There is no limit to the size of the data you can analyze locally on your machine on Power BI Desktop. You will be constrained only by the memory capacity of your machine, as Power BI Desktop, at a minimum, uses the same amount of memory as the data model size. The limitations would apply only when you decide to publish a report to the Power BI service and collaborate and distribute the report to other users/audiences.

Publishing to the Power BI service using a free license

Is it possible to publish to the Power BI service for free? Yes, it is possible. Let’s dive into the details.

To log in to the Power BI service, you need a Power BI free license. By default, when you sign in to powerbi.com, if your organization (that is, your M365 administrator) has not blocked self-service signup for Power BI, you will be granted a Power BI free license automatically. You can check the license assigned to you by your organization after your successful sign in to powerbi.com. After signing in, click on the user icon in the top-right corner of the screen to check the license type.

Figure 2.1 – A Power BI license check

If the M365 administrators have blocked self-service signup to Power BI and you are unable to log in to Power BI, ask the M365 team to assign a free license to you, allowing you to explore Power BI. Your M365 administrator could assign a Power BI free license from the M365 admin portal (admin.microsoft.com), as explained in https://learn.microsoft.com/en-us/power-bi/enterprise/service-admin-licensing-organization#about-self-service-sign-up.

With a Power BI free license, you can publish your report to the Power BI service but not collaborate or share it with others. Once the free license is assigned to a user, the user can publish reports to a workspace, called My workspace. This is a workspace that is created by default by Power BI for every Power BI user. My workspace is a private space for each user, and one user’s workspace is not visible to another. Power BI users with free licenses are allowed to publish to My workspace only and not any other workspace.

Using a Power BI free license, you can publish reports, create dashboards, and set up a schedule to refresh a semantic model, but only inside My workspace, which can’t be shared with anyone else. Also, the semantic model size used can’t exceed 1 GB in My workspace.

Now that we have covered the capabilities of a Power BI free license, let’s cover the capabilities of the most basic paid license in Power BI, the Power BI Pro license, in the next section.

The Power BI Pro license