You are previewing Data Visualization For Dummies.
O'Reilly logo
Data Visualization For Dummies

Book Description

A straightforward, full-color guide to showcasing data so your audience can see what you mean, not just read about it

Big data is big news! Every company, industry, not-for-profit, and government agency wants and needs to analyze and leverage datasets that can quickly become ponderously large. Data visualization software enables different industries to present information in ways that are memorable and relevant to their mission. This full-color guide introduces you to a variety of ways to handle and synthesize data in much more interesting ways than mere columns and rows of numbers.

Learn meaningful ways to show trending and relationships, how to convey complex data in a clear, concise diagram, ways to create eye-catching visualizations, and much more!

  • Effective data analysis involves learning how to synthesize data, especially big data, into a story and present that story in a way that resonates with the audience

  • This full-color guide shows you how to analyze large amounts of data, communicate complex data in a meaningful way, and quickly slice data into various views

  • Explains how to automate redundant reporting and analyses, create eye-catching visualizations, and use statistical graphics and thematic cartography

  • Enables you to present vast amounts of data in ways that won't overwhelm your audience

Part technical manual and part analytical guidebook, Data Visualization For Dummies is the perfect tool for transforming dull tables and charts into high-impact visuals your audience will notice...and remember.

Table of Contents

    1. Introduction
      1. About This Book
      2. Foolish Assumptions
      3. Icons Used in This Book
      4. Beyond the Book
      5. Where to Go from Here
    2. Part I: Getting Started with Data Visualization
      1. Chapter 1: Introducing Data Visualization
        1. Understanding Data Visualization
          1. Understanding the importance of data viz
          2. Discovering who uses data viz
        2. Recognizing the Traits of Good Data Viz
        3. Embracing the Design Process
        4. Ensuring Excellence in Your Data Visualization
      2. Chapter 2: Exploring Common Types of Data Visualizations
        1. Understanding the Difference between Data Visualization and Infographics
        2. Picking the Right Content Type
        3. Appreciating Interactive Data Visualizations
        4. Observing Visualizations in Different Fields
        5. Using Dashboards
        6. Discovering Infographics
          1. Examining different types of infographics
          2. Taking advantage of online infographic tools
      3. Chapter 3: Knowing What You Must about Big Data
        1. Defining Big Data
        2. Seeing How Big Data Changes Business
          1. Getting to know your customers
          2. Discovering the Four V's
          3. Collecting structured and unstructured data
          4. Ensuring the use of quality data
        3. Avoiding Dying by Tool Choice
          1. Tableau
    3. Part II: Mastering Basic Data Visualization Concepts
      1. Chapter 4: Using Charts Effectively
        1. Deciding Which Charts to Use and When to Use Them
          1. Understanding where newbies should start
          2. Choosing simple and effective charts
          3. Using gauges and scorecards to monitor
          4. Finding online tools for chart making
        2. Dipping Into Less-Common Charts
      2. Chapter 5: Adding a Little Context
        1. Making Text Useful
          1. Adding text labeling
          2. Considering text positioning
          3. Choosing text fonts
          4. Choosing text color
        2. Exploring Text Analysis
          1. Determining what makes text analysis so important
          2. Building a text analysis statement
      3. Chapter 6: Paying Attention to Detail
        1. Uncovering How People Digest Data
        2. Presenting Common Visual Patterns
          1. Z and F patterns
          2. Pattern design
        3. Deciding to Use a Template
        4. Achieving Consistency across Devices
          1. Embracing responsive design
          2. Following app design standards
    4. Part III: Building Your First Data Visualization
      1. Chapter 7: Defining an Easy-to-Follow Storyboard
        1. Business Intelligence Overview
        2. Delving Into Your Story
          1. Uncovering storyboard content
          2. Identifying your audience
          3. Documenting Goals
          4. Documenting KPIs
        3. Building Your First Storyboard
          1. Section 1: Current State
          2. Section 2: Trends
          3. Section 3: Forecast
          4. Section 4: What-if
      2. Chapter 8: Developing a Clear Mock-Up
        1. Getting Started with Your Mock-Up
          1. Sticking to black and white
          2. Using good ol’ pencil and paper
          3. Using web-based or desktop tools
        2. Building Template Layouts
      3. Chapter 9: Adding Effective Visuals to Your Mock-Up
        1. Recognize the Three Traits of an Effective Visual
          1. Data is clear
          2. Visual fits the data
          3. Exceptions are easy to spot
        2. Focus on Insight, Not Hindsight
        3. Add Visuals to Your Mock-Up
          1. Section 1: Current State
          2. Section 2: Trends
          3. Section 3: Forecast
          4. Section 4: What-If
      4. Chapter 10: Adding Functionality and Applying Color
        1. Recognizing the Human Components
          1. Humanizing your visualizations
          2. Thinking mobile first
          3. Adding functionality
          4. Choosing navigation by using rules
          5. Identifying the most popular menu types
        2. Dipping Into Color
          1. Taking advantage of company branding guidelines
          2. Choosing colors without guidelines
          3. Using RAG colors
      5. Chapter 11: Adding Some Finishing Touches
        1. Choosing Useful Links
          1. Introducing six mandatory links
          2. Including a last updated timestamp
        2. Adding Legal Stuff
          1. Embracing the copyright
          2. Delving into terms and conditions
        3. Discovering Visual Cues
        4. Adding Location Intelligence
      6. Chapter 12: Exploring User Adoption
        1. Understanding User Adoption
        2. Considering Five UA Measurements
        3. Marketing to Data Viz Users
          1. Ensure data availability and accuracy
          2. Use buy-in and ownership to engage users
          3. Give each data viz the right name
          4. Use internal social media platforms and intranets
          5. Go live on internal platforms
          6. Do away with training
          7. Make sure that the data viz looks great
          8. Provide 24/7 accessibility
          9. Provide speed and reliability
          10. Speed the delivery of your data viz
    5. Part IV: Putting Data Viz Techniques into Practice
      1. Chapter 13: Evaluating Real Data Visualizations
        1. Analyzing Data Visualizations by Category
          1. Big-picture considerations
          2. Color
          3. Design issues
          4. Text formatting
          5. Menus
          6. Interactivity
          7. Design for mobile
        2. Evaluating Data Visualizations
          1. Data visualization 1
          2. Data visualization 2
          3. Data visualization 3
          4. Data visualization 4
          5. Data visualization 5
          6. Data visualization 6
          7. Data visualization 7
          8. Data visualization 8
          9. Data visualization 9
          10. Data visualization 10
          11. Data visualization 11
          12. Data visualization 12
      2. Chapter 14: Recognizing Newbie Pitfalls
        1. Going Overboard with Data
        2. Falling into the One-Shoe-Fits-All Trap
        3. Focusing on the Tool Instead of the Story
        4. Building Mobile Last
        5. Abusing Pie Charts
        6. Using Green for Alerts
        7. Ignoring Basic Statistics
          1. Knowing the probability that an event will occur
          2. Applying variance to show the magnitude of change
          3. Forecasting the future
        8. Not Mastering User Engagement
    6. Part V: The Part of Tens
      1. Chapter 15: Top Ten Data Visualization Resources
        1. Edward Tufte
        3. The Functional Art
        4. Visualizing Data
        5. Chart Porn
        6. The Excel Charts Blog
        7. FlowingData
        9. GE Data Visualization
        10. #dataviz and #bigdata
      2. Chapter 16: Top Ten Fears of New Data-Viz Creators
        1. Telling the Wrong Story
        2. Creating an Ugly Data Viz
        3. Picking the Wrong Things to Measure
        4. Alienating Other Stakeholders
        5. Misunderstanding the Audience for Your Data Viz
        6. Forgetting about Copyrights and Legal Matters
        7. Selecting the Wrong Tool
        8. Making the Wrong Chart Choices
        9. Picking Bad/Noncomplementary Colors
        10. Using Too Much Data
    7. About the Authors
    8. More Dummies Products