Microsoft Power BI Data Analyst Associate Study Guide. Prepare for the PL-300 Exam and Use Power BI Successfully Paul Turley

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Spis treści książki

• 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

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