Learning Microsoft Power BI

Learning Microsoft Power BI

by Jeremey Arnold
Released September 2022
Publisher(s): O'Reilly Media, Inc.
ISBN: 9781098112844

Read it now on the O’Reilly learning platform with a 10-day free trial.

O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.

Buy on Amazon Buy on ebooks.com
Start your free trial

Book description

Microsoft Power BI is a data analytics and visualization tool powerful enough for the most demanding data scientists, but accessible enough for everyday use for anyone who needs to get more from data. The market has many books designed to train and equip professional data analysts to use Power BI, but few of them make this tool accessible to anyone who wants to get up to speed on their own.

This streamlined intro to Power BI covers all the foundational aspects and features you need to go from "zero to hero" with data and visualizations. Whether you work with large, complex datasets or work in Microsoft Excel, author Jeremey Arnold shows you how to teach yourself Power BI and use it confidently as a regular data analysis and reporting tool.

You'll learn how to:

  • Import, manipulate, visualize, and investigate data in Power BI
  • Approach solutions for both self-service and enterprise BI
  • Use Power BI in your organization's business intelligence strategy
  • Produce effective reports and dashboards
  • Create environments for sharing reports and managing data access with your team
  • Determine the right solution for using Power BI offerings based on size, security, and computational needs

Publisher resources

View/Submit Errata

Table of contents

  1. Preface
    1. Navigating This Book
    2. Conventions Used in This Book
    3. Using Code Examples
    4. O’Reilly Online Learning
    5. How to Contact Us
    6. Acknowledgments
  2. 1. Intro to Power BI
    1. What Is Power BI?
      1. Power BI Components
      2. Power BI Desktop
      3. The Power BI Service
      4. The Power Platform
    2. How Did We Get to Power BI?
      1. SQL Server: Microsoft’s Relational Database
      2. SQL Server Analysis Services Multidimensional: One Small Step into BI
      3. SQL Server Reporting Services: Pixel-Perfect Reporting, Automated Reports, and More
      4. Excel: A Self-Service BI Tool
      5. Power Pivot
      6. Important New Functionality That Leads to Power BI
      7. Power BI Desktop Is Born
    3. Power BI Desktop Under the Hood
      1. VertiPaq: The Storage Engine
      2. DAX: The Formula Engine
    4. What Makes Power BI Different from Its Competitors?
    5. Conclusion
  3. 2. The Report and Data Views
    1. Report View: Home Section of the Ribbon
      1. The Clipboard Subsection
      2. The Data Subsection
      3. The Queries Subsection
      4. The Insert Subsection
      5. The Calculations Subsection
      6. The Final Subsections: Sensitivity and Share
    2. Report View: The Insert Tab
      1. The Pages Subsection
      2. The Visuals Subsection
      3. The AI Visuals Subsection
      4. The Power Platform Subsection
      5. The Elements Subsection
    3. Report View: The Modeling Tab
      1. The Relationships Subsection
      2. The Calculations Subsection
      3. The Page Refresh Subsection
      4. The What If Subsection
      5. The Security Subsection
      6. The Q&A Subsection
    4. Report View: The View Tab
      1. The Themes Subsection
      2. The Scale to Fit Subsection
      3. The Page Options Subsection
      4. The Show Panes Subsection
    5. Report View: Help Section
    6. Report View: External Tools Section
    7. The Pane Interface of the Report View
      1. Visualizations Pane
      2. Fields and Filters Panes
      3. A Quick Rundown of the Other Panes
    8. Data View
    9. Conclusion
  4. 3. Importing and Modeling Our Data
    1. Getting Our Data
    2. The Power Query Ribbon
      1. The Home Tab
      2. The Transform Tab
      3. The Add Column Tab
    3. The Model View
      1. What Is a Relationship?
      2. The Properties Pane
    4. Conclusion
  5. 4. Let’s Make Some Pictures (Visualizing Data 101)
    1. Why Visualize Data?
    2. The Visualizations Pane
      1. Fields
      2. Format
      3. Analytics
    3. Visual Interactivity
    4. Column and Bar Charts
      1. Stacked Bar and Column Charts
      2. Clustered Bar and Column Charts
      3. 100% Stacked Bar and Column Charts
      4. Small Multiples
      5. Waterfall Chart
    5. Line and Area Charts
      1. Line Chart
      2. Area Chart
      3. Stacked Area Chart
      4. Line and Stacked Column Chart/Clustered Column Chart
      5. Ribbon Chart
    6. Donuts, Dots, and Maps, Oh My!
      1. Funnel Chart
      2. Scatter Chart
      3. Pie and Donut Chart
      4. Treemap
      5. Map Visuals
    7. The “Flat” Visuals
      1. Gauge
      2. Card/Multi-Row Card
      3. KPI
      4. Table/Matrix
      5. Slicer
    8. Conclusion
  6. 5. Aggregations, Measures, and DAX
    1. A Primer on the DAX Language
      1. Measures
      2. Calculated Columns
      3. Calculated Tables
      4. Types of Functions
    2. Aggregations, More Than Some Sums
      1. Sum
      2. Average
      3. Minimum and Maximum
      4. Standard Deviation, Variance, and Median
      5. Count and Count (Distinct)
      6. First, Last, Earliest, and Latest
    3. Measures and DAX Fundamentals
      1. Implicit and Explicit Measures
      2. DAX Syntax Fundamentals
      3. CALCULATE
      4. We Heard You Like DAX, So We Put Some DAX in Your DAX
      5. Row and Filter Context
      6. One Final DAX Example
    4. Conclusion
  7. 6. Putting the Puzzle Pieces Together: From Raw Data to Report
    1. Your First Data Import
      1. Choose and Transform the Data When You Import
      2. Transformations in Power Query
    2. Second Data Import and Wrangling
      1. Consolidating Tables with Append
      2. Using Merge to Get Columns from Other Tables
    3. Building Relationships
      1. Hiding Tables
      2. Identifying Our Relationship Columns
      3. Time to Get Building
    4. Let’s Get Reporting!
      1. We Need a Name...
      2. Cards Help Identify Important Data Points
      3. Bars, Columns, and Lines
      4. Conclusion
  8. 7. Advanced Reporting Topics in Power BI
    1. AI-Powered Visuals
      1. Key Influencers
      2. Decomposition Tree
      3. Q&A
      4. Smart Narrative
    2. What-If Analysis
      1. Parameter Setup
      2. DAX Integration of the Parameter
      3. Parameter Modification
    3. R and Python Integration
      1. Limitations of Using R and Python
      2. Enabling R and Python for Power BI
      3. R and Python in Power Query
      4. R and Python Visuals
    4. Conclusion
  9. 8. Introduction to the Power BI Service
    1. The Basics of the Service: What You Need to Know
    2. The Navigation Menu
      1. Home and Browse
      2. Create
      3. Data Hub
      4. Settings
      5. Metrics
      6. Apps
      7. Deployment Pipelines
      8. Learn
    3. Publishing Your Work
    4. What Is a Workspace?
      1. My Workspace
      2. Shared Capacity Workspaces
      3. Dataflows in Shared Workspaces
    5. Putting Your Data in Front of Others
      1. Adding Users to a Workspace
      2. Sharing via a Link or Teams
      3. Sharing via SharePoint
      4. Creating an App
    6. Conclusion
  10. 9. Licensing and Deployment Tips
    1. Licensing
      1. Pro Licensing
      2. Premium Per User Licensing
      3. Premium Per Capacity, the Big Boy
    2. Workspace and App Management
      1. Workspace Generation and Access Control
      2. Managing Users in a Workspace
      3. Adding Users to Roles for RLS Implementation
      4. App Creation and Management
      5. The Golden Dataset(s)
    3. Conclusion
  11. 10. Third-Party Tools
    1. Get to Know Business Ops
      1. Add External Tools, Remove External Tools, and Modify Display Order
      2. Learning, Theme Generation, Visual Generation
      3. Additional DAX Resources
    2. DAX Studio
    3. Tabular Editor
      1. Creating Roles
      2. Table and Measure Management
    4. The ALM Toolkit for Power BI
    5. Bravo
      1. Analyze Model
      2. DAX Formatting
      3. Manage Dates
      4. Export Data
    6. Conclusion
  12. A. Commonly Used DAX Expressions
    1. Aggregation Functions
      1. AVERAGE
      2. AVERAGEX
      3. COUNT
      4. DISTINCTCOUNT
      5. MAX
      6. MAXX
      7. MIN
      8. MINX
      9. SUM
      10. SUMX
      11. PRODUCT
      12. PRODUCTX
    2. Date and Time Functions
      1. CALENDAR
      2. DATEDIFF
      3. DAY
      4. MONTH
      5. TODAY
      6. YEAR
    3. Time Intelligence Functions
      1. DATEADD
      2. DATESMTD
      3. DATESQTD
      4. DATESYTD
    4. Filter Functions
      1. ALL
      2. ALLEXCEPT
      3. CALCULATE
    5. Logical Functions
      1. AND
      2. COALESCE
      3. IF
      4. OR
    6. DAX Operators
  13. B. Some Favorite Custom Visuals
    1. Adding Custom Visuals to Power BI Desktop
    2. Ten of My Favorite Custom Visuals
      1. Advance Card
      2. Chiclet Slicer
      3. Drilldown Choropleth
      4. Forecasting with ARIMA
      5. Gantt Chart
      6. Radar Chart
      7. Route Map
      8. Scroller
      9. Sunburst Chart
      10. Word Cloud
    3. Charticulator
  14. Index
  15. About the Author

Product information

  • Title: Learning Microsoft Power BI
  • Author(s): Jeremey Arnold
  • Release date: September 2022
  • Publisher(s): O'Reilly Media, Inc.
  • ISBN: 9781098112844