Storytelling with data : a data visualization guide for business professionals /

Sometimes it is easy to generate charts and graphs look fine to you, but don't clearly communicate the information that they represent. Knaflic's own knack for clarity will help you sharpen your message when using data in your business presentations.

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Bibliographic Details
Main Author: Knaflic, Cole Nussbaumer (Author)
Format: Electronic eBook
Language:English
Published: Hoboken, New Jersey : Wiley, [2015]
Subjects:
Online Access: Full text (Wentworth users only)
Table of Contents:
  • Title page
  • Copyright
  • Dedication
  • Foreword
  • Note
  • Acknowledgments
  • About the Author
  • Introduction
  • Bad graphs are everywhere
  • We aren't naturally good at storytelling with data
  • Who this book is written for
  • How I learned to tell stories with data
  • How you'll learn to tell stories with data: 6 lessons
  • Illustrative examples span many industries
  • Lessons are not tool specific
  • How this book is organized
  • Chapter 1 the importance of context
  • Exploratory vs. explanatory analysis
  • Who, what, and how
  • Who
  • What
  • How.
  • Who, what, and how: illustrated by example
  • Consulting for context: questions to ask
  • The 3-minute story & Big Idea
  • Storyboarding
  • In closing
  • Chapter 2 choosing an effective visual
  • Simple text
  • Tables
  • Graphs
  • Points
  • Lines
  • Bars
  • Area
  • Other types of graphs
  • To be avoided
  • In closing
  • Chapter 3 clutter is your enemy!
  • Cognitive load
  • Clutter
  • Gestalt principles of visual perception
  • Lack of visual order
  • Non-strategic use of contrast
  • Decluttering: step-by-step
  • In closing
  • Chapter 4 focus your audience's attention
  • You see with your brain.
  • A brief lesson on memory
  • Preattentive attributes signal where to look
  • Size
  • Color
  • Position on page
  • In closing
  • Chapter 5 think like a designer
  • Affordances
  • Accessibility
  • Aesthetics
  • Acceptance
  • In closing
  • Chapter 6 dissecting model visuals
  • Model visual #1: line graph
  • Model visual #2: annotated line graph with forecast
  • Model visual #3: 100% stacked bars
  • Model visual #4: leveraging positive and negative stacked bars
  • Model visual #5: horizontal stacked bars
  • In closing
  • Chapter 7 lessons in storytelling
  • The magic of story
  • Constructing the story.
  • The narrative structure
  • The power of repetition
  • Tactics to help ensure that your story is clear
  • In closing
  • Chapter 8 pulling it all together
  • Lesson 1: understand the context
  • Lesson 2: choose an appropriate display
  • Lesson 3: eliminate clutter
  • Lesson 4: draw attention where you want your audience to focus
  • Lesson 5: think like a designer
  • Lesson 6: tell a story
  • In closing
  • Chapter 9 case studies
  • CASE STUDY 1: Color considerations with a dark background
  • CASE STUDY 2: Leveraging animation in the visuals you present
  • CASE STUDY 3: Logic in order.
  • CASE STUDY 4: Strategies for avoiding the spaghetti graph
  • CASE STUDY 5: Alternatives to pies
  • In closing
  • Chapter 10 final thoughts
  • Where to go from here
  • Building storytelling with data competency in your team or organization
  • Recap: a quick look at all we've learned
  • In closing
  • Bibliography
  • Index
  • EULA.