Passing the PL-300 exam with 2025 revisions isn't just about memorization—you need to thoroughly know the basic features of Power BI. However, data professionals must also apply best practices that make Power BI solutions scalable and future-proof. The first half of this go-to companion by Paul Turley provides complete coverage of the PL-300 exam objectives for desktop and self-service users, while the second half equips you with necessary best practices and practical skills for real-world success after the exam.

Immerse yourself in exam prep, practice questions, and hands-on references for applying time-tested design patterns in Power BI. You'll learn how to transform raw data into actionable insights using Power Query, DAX, and dimensional modeling. Perfect for data analysts and business intelligence developers, this guide shows how Power BI fits into modern data platforms like Azure and Microsoft Fabric, preparing you for the exam and for the evolving world of data engineering.

• Understand PL-300 exam topics and key prep strategies
• Use best practices to discover scalable, enterprise-grade Power BI solutions
• Learn how to correctly apply Power Query, DAX, and visualizations in real-world scenarios with real business data
• Uncover how to build for scale
• See how Power BI fits into modern architectures like Azure and Microsoft Fabric

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Spis treści

Microsoft Power BI Data Analyst Associate Study Guide. Prepare for the PL-300 Exam and Use Power BI Successfully eBook -- spis treści

• Preface
  • Conventions Used in This Book
  • Using Code Examples
  • OReilly Online Learning
  • How to Contact Us
  • Acknowledgments
• I. Preparing to Take and Pass the PL-300 Exam
• 1. Successful Test Taking
  • Why Are You Taking This Exam?
    • A Very Short History Lesson
    • Power BI and Fabric Roles
  • Why Did I Write This Book?
  • Ethics and Integrity
  • Delivery Options: Proctored or in Person?
    • Test Center Delivery
      • Online proctored delivery
    • Timing and Expectations
    • Can You Take a Break?
  • The Psychology of Testing
    • Know Your Learning Style
    • Personality-Based Exam Preparation
      • E versus I
      • S versus N
      • T versus F
      • J versus P
    • Make Your Plan
  • Question Patterns and Testing Strategies
    • Multiple Choice and Statistical Probability
    • Navigating Case Studies and Scenarios
    • Solution Series Questions
  • Summary
• 2. Preparing Data
  • Optimizing and Iterating
  • Power Query and Get Data
  • Data Transformations
  • Data Sources and Connections
    • Storage Modes
    • Connection Properties
    • Data Source Parameters
    • Filtering and Parameters
  • Organizing and Reusing Queries
  • Assessing and Improving Data Quality
  • Data Profiling
  • Combining Data
  • Query Optimization
  • Summary
  • Practice Exam Questions
• 3. Modeling Data
  • The Semantic Data Model
    • The VertiPaq Engine
    • Storage Modes
      • Import mode
      • DirectQuery mode
      • Dual mode
    • Compression and Encoding
  • Dimensional Modeling
    • Relationship Cardinality
    • Filter Propagation
    • Date Tables
      • Special calendar and accounting periods
    • Role-Playing Dimensions
    • Column Properties and Settings
    • DAX Essentials
      • Measures
      • DAX function types
        • Aggregations
        • Filters and context
        • Time intelligence
      • Measure properties and settings
      • Calculated columns
      • Calculated tables
      • DAX queries
      • Performance Analyzer and DAX query view
    • Advanced Model Features
      • Calculation groups
      • Row-level security
        • Filter propagation and RLS
      • Role-based RLS
        • Dynamic RLS
      • Incremental refresh
        • Requirements
  • Summary
  • Practice Exam Questions
• 4. Visualizing and Presenting Data
  • Analysis and Reporting
    • Visual Report Types
      • Power BI interactive reports
      • Static and operational reports
      • Paginated reports
      • Accounting and financial planning reports
      • Analyze in Excel
      • Scorecards and metrics
      • Dashboards
      • Data storytelling
    • Visual Design with Theme and Color Selection
    • Interactive Reporting
      • Mobile reporting
      • Visual interactions
      • Drilldown navigation
      • Drillthrough navigation
      • Tooltips
    • Visual Storytelling
    • Natural Language Enhancements
      • Q&A
      • Narratives
  • Visual Types and Selection Criteria
    • Scalar Values and Performance Indicators
    • Comparison and Clustering
    • Series and Trend Analysis
    • Parts of a Whole
    • Geographical Correlation
    • Custom Visuals
    • Slicers and Filters
    • Bookmarks
    • Conditional Formatting and Visual Enhancements
    • Hierarchies and Groups
    • Advanced and Specialized Visuals
    • Patterns, Trends, and Outliers
  • Summary
  • Practice Exam Questions
• 5. Deploying and Maintaining Power BI Solutions
  • Accessing Power BI Content
    • Sharing a Report with Users
    • Embedding Options
    • Managing Content with Workspaces
      • Workspace apps
      • Creating items in the Power BI portal
      • Paginated reports
      • Scorecard
      • Real-time dashboards
      • Apps and audiences
    • Publishing Content
    • Dashboards
    • Metrics and Scorecards
    • User and Developer Access
    • Workspace Apps
    • Exploring Data
  • Managing Connections
    • On-Premises Gateway
    • Lineage View
    • Refreshing Models in the Service
    • Report Subscriptions and Alerts
  • Data Governance, Protection, and Discovery
    • OneLake Catalog
    • Endorsements and Certified Items
    • Sensitivity Labels
    • Semantic Model Roles and RLS
      • Static RLS
      • Dynamic RLS
  • Power BI Report Server
  • Summary
  • Practice Exam Questions
    • Delivering Content
    • Deploying and Managing
• II. Using Power BI in the Real World
• 6. Planning and Architecting Enterprise Power BI Solutions
  • Business Intelligence Solution Architecture
  • Understanding the Three Vs of Data
  • Power BI and Microsoft Fabric
    • Building BI Solutions on Modern Data Architecture
    • No More Throwing Projects over the Wall
    • Scenario A: Isolated Power BI Projects
    • Scenario B: Conventional Data Warehouse and Power BI Solutions
    • Scenario C: Enterprise BI and Self-Service Reporting
    • Scenario D: Introducing the Analyst Engineer
    • Data Preparation and Data Engineering in Microsoft Fabric
      • Data factory pipelines
      • Notebooks
      • Dataflow Gen2
  • Power BIs Development Environment
    • Power BI Desktop Options
    • Development Extensions and Community Tools
  • Version Control for Power BI
    • Version Control and Fabric Git Integration
    • The Power BI DevOps Journey
    • DevOps and CI/CD Terminology
    • Some Thoughts and Advice About DevOps for BI
  • Release Management Using Deployment Pipelines
  • Setting Up a GitHub Repo and Power BI Project
    • Install the GitHub Distribution
    • Create a Local Repo Folder
    • Creating the Local Repository
    • Managing the Project with Visual Studio Code
    • Merging and Resolving Conflicts
    • Syncing Changes
  • Summary
• 7. Enterprise Power Query Best Practices
  • Power Query and Dataflows
  • The Importance of Query Folding
  • Example 1: Importing Data from Text Files
    • The Sample Data
    • The Ever-Changing Power Query Design Interface
    • Lets Get Started
    • Create Airline Performance Base Query
    • Addressing a Data Quality Problem
    • Create and Use Parameters
    • Create the Airline Carriers Query
    • Import and Transform Queries
      • Origin Airports
      • Destination Airports
      • Airlines
    • Create the Flight Date Table
    • Transforming the Airline Performance Query
    • Fix All the Midnights
    • Loading the Query Data
  • Example 2: Importing Data from a Database
    • Scaling Queries with Incremental Refresh
    • What Have We Learned?
  • Summary and Best Practices Review
• 8. Semantic Model Development
  • Modeling Essentials and Guidelines
  • Collecting Model Requirements
    • Use Cases
    • Metric and Measure Requirements
    • Dimensional Bus Matrix
    • Whats in a Name?
    • Field Naming Conventions
    • Hidden Columns, Implicit Measures, and Summarization
  • Naming Conventions
    • Query and Table Names
    • Query Group Names
    • Parameter Names
    • Power Query Functions
    • Visible and Hidden Field Names
    • Model Table Names
    • Measure Names
    • Extended Characters in Measure Names
    • Measure Variable Names
  • Modeling Imported Tables
    • Mark Date Table
    • Cardinality and Cross-Filter Direction
    • Creating Relationships
    • You Cant Always Get What You Want
    • You Just Might Find You Get What You Need
  • Measures 101
    • Base Measures
    • Layered Measures
    • Calculation Groups
  • Star Schema Exceptions and Enhancements
    • Ambiguous Relationships
    • Bidirectional Relationship Filters
    • Many-to-Many Relationships
    • Supporting Transaction and Detail Tables
  • Setting Field and Measure Properties
    • Measure Tables
    • Display Folders
    • Data Categories
    • Advanced Property Management
    • Model Object Properties
      • Table properties
      • Field and column properties
      • Measure properties
      • Hierarchy properties
  • Managing Changes
  • Cleaning and Decluttering Models
  • AI Integration and Copilot for Power BI
  • Preparing Data for Copilot
    • Verified answers
  • Summary and Best Practices Review
  • Model Design Checklist
• 9. Report Design Patterns and Techniques
  • Audience and Purpose: Balancing Form, Fit, and Function
  • Cognitive Perception and Information Processing
    • Reading Patterns
    • The Data-to-Ink Ratio
    • The Gestalt Principles
    • Segmentation and Series
    • A Few Bad Examples
    • Proportions and Pie Charts
  • Designing a Report Page
  • Report Navigation
    • Drilldown Navigation
    • Drillthrough Navigation
    • Tooltip Pages
  • Paginated Reports
    • Drilling Through to Paginated Reports
    • Passing Parameters
    • Background
    • Paginated Report Designer
    • To Model or Not to Model?
  • Summary and Best Practices Review
  • Report Visual Design Checklist
• A. Solutions to the Practice Questions
  • Chapter 2
  • Chapter 3
  • Chapter 4
  • Chapter 5
    • Delivering Content
    • Deploying and Managing
• Index