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Data is a fantastic raw resource for powering change in an organization, but all too often the people working in those organizations don't have the necessary skills to communicate with data effectively. With this practical book, subject matter experts will learn ways to develop strong, persuasive points when presenting data to different groups in their organizations.

Author Carl Allchin shows anyone how to find data sources and develop data analytics, and teaches those with more data expertise how to visualize data to convey findings to key business leaders more effectively. Once your business and data experts both possess the skills to work with data and interpret its significance, you can deal with questions and challenges in departments across your organization.

  • Learn the fundamental data skills required to work with data
  • Use data visualization to influence change in your organization
  • Learn how to apply data techniques to effectively work with data end to end
  • Understand how to communicate data points clearly and persuasively
  • Appreciate why different stakeholders often have divergent needs and views
  • Create a playbook for using data with different departments

Table of Contents

  1. Preface
    1. Why I Wrote This Book
    2. Who Is This Book For?
    3. How the Book Is Organized
    4. Conventions Used in This Book
    5. Using Code Examples
    6. O’Reilly Online Learning
    7. How to Contact Us
    8. Acknowledgements
  2. 1. Communication
    1. What Is Communication?
    2. The Communication Process
    3. Getting Through to Your Audience: Context and Noise
    4. Don’t Forget About Memory
    5. Why Visualize Data?
    6. Pre-Attentive Attributes in Action
    7. Unique Considerations
    8. Summary
  3. 2. Data
    1. What Is Data?
    2. The Key Features of Data
    3. Rows and Columns
    4. Data Types
    5. How Is Data Created?
    6. Where Is Data Created?
    7. Should You Trust Your Data?
    8. Data As a Resource
    9. Files
    10. Databases, Warehouses, and Lakes
    11. Application Programming Interfaces (APIs)
    12. Data Security and Ethics
    13. Easy or Hard? the “Right” Data Structure
    14. The Shape of Data
    15. Cleaning Data
    16. The “Right” Data
    17. Requirement Gathering
    18. Use of the Data
    19. Summary
  4. 3. Visualizing Data
    1. Tables
    2. How to Read Tables
    3. How to Optimize Tables
    4. When You Might Not Use Tables
    5. Bar Charts
    6. How to Read Bar Charts
    7. How to Optimize Bar Charts
    8. When You Might Not Want to Use Bar Charts
    9. Line Charts
    10. How to Read Line Charts
    11. How to Optimize Line Charts
    12. When You Might Not Use Line Charts
    13. Summary
  5. 4. Visualizing Data Differently
    1. Chart Types - Scatterplots
    2. How to Read Scatterplots
    3. How to Optimize Scatterplots
    4. When to Avoid Scatterplots
    5. Chart Types - Maps
    6. How to Read Maps
    7. How to Optimize Maps
    8. When You Might Not Use Maps
    9. Chart Types - Part-To-Whole
    10. How to Read
    11. When to Use
    12. When You Might Not Use Part-To-Whole Charts
    13. Summary
  6. 5. Visual Elements
    1. Color
    2. Types of Color Palette
    3. Choosing the ‘Right’ Color
    4. Avoiding Unnecessary Use of Color
    5. Size and Shape
    6. Themed Charts
    7. Size and Shape Challenges
    8. Multiple Axes
    9. Reference Lines/ Bands
    10. Reference Lines
    11. Reference Bands
    12. Totals/Summaries
    13. Totals in Tables
    14. Totals in Charts
    15. Summary
  7. 6. Methods of Communicating with Data
    1. Explanatory Communications
    2. Gathering Requirements
    3. Updating Data in Explanatory Views
    4. So What?
    5. Exploratory Communications
    6. Gathering Requirements
    7. Flexibility and Flow
    8. Dashboards
    9. Monitoring Conditions
    10. Facilitating Understanding
    11. Infographics
    12. Slide Presentations
    13. Notes and Emails
    14. Summary
  8. 7. Implementation Strategies for Your Workplace
    1. Tables Versus Pretty Pictures
    2. Data Culture
    3. Data Literacy
    4. Improving the Visualization Mix
    5. Static Versus Interactive
    6. Let’s Talk About Powerpoint
    7. More Than Just Powerpoint
    8. Easier Production
    9. Interactive User Experience
    10. Centralized Versus Decentralized Data Teams
    11. The Data Team
    12. Data Sources
    13. Reporting
    14. Pooling Data Expertise
    15. Self-Service
    16. Live Versus Extracted Data
    17. Live Data
    18. Extracted Data Sets
    19. Standardization Versus Innovation
    20. Importance of Standardization
    21. Importance of Innovation
    22. Reporting Versus Analytics
    23. Reporting - Mass Production
    24. Analytics - Flexibility but Uncertainty
    25. Finding the ‘Perfect’ Balance
    26. Summary
  9. 8. Tailoring Your Work to Specific Departments
    1. The Executive Team
    2. Finance
    3. Human Resources
    4. Operations
    5. Marketing
    6. Sales
    7. Information Technology
    8. Summary