Data Visualization: Storytelling Using Data

Description

Data Visualization: Storytelling Using Data explains data insights through visuals and show how to make them compelling and comprehensible through a series of realworld examples. It provides a roadmap that covers everything from understanding “why data visualization and storytelling are important” to learning “how to visualize data and communicate it to an audience effectively”. This book attempts to provide students and industry professionals with a practical method for mastering data storytelling skills.

About the Author

Sharada Sringeswara is an adjunct faculty member at the Indian Institute of Management Bangalore – Data Centre and Analytics Lab (IIMB–DCAL) and Associate Partner at Acuver Consulting Private Limited. Currently She is a seasoned analytics executive with hands-on and leadership experience in building business models with an understanding of the digital technology landscape.

Purvi Tiwari is a research associate at IIMB-DCAL. She has a master’s degree focused on Applied Mathematics from the Indian Institute of Science Education and Research, Pune (IISER-Pune). She has a strong research working experience with a demonstrated history in the higher education industry, specializing in mathematical modelling, statistical modelling, Monte Carlo–Markov Chain (MCMC), machine learning, and deep learning.

U Dinesh Kumar is a Professor of Decision Sciences at IIM Bangalore and Chairperson of MBA (Business Analytics), he is also IIMB chair of excellence since January 2020. He holds a doctorate in Mathematics from IIT Bombay. Dr Kumar introduced Business Analytics elective course in 2008 to PGP students at IIMB and started one of the first certificate programs in Business Analytics in India in 2010.

Table of Contents

Book Review

Preface

About the Authors

Acknowledgement

Chapter 1 Introduction to Visualization

1.1 What Is Data Visualization?

1.2 Why Do We Have to Visualize Data?

1.3 How Do We Visualize?

1.4 Seven Stages of Visualizing Data

1.5 Usage of Visualization

1.6 Types of Charts

1.7 Common Chart Selection Questions

Chapter 2 Visualization Best Practices

2.1 Importance of Data Visualization

2.2 Data Types

2.3 Effectiveness of Visual Encodings

2.4 Color

2.5 Edward Tufte’s Design Principles

2.6 Can Chart Junk be Useful?

Chapter 3 Visualization of Structured Data

3.1 Introduction

3.2 Exploratory Analysis

3.3 Modelling

3.4 Visualization during Deployment

3.5 Business Operation Dashboard

Chapter 4 Visualization of Unstructured Data

4.1 Introduction

4.2 Importance of Text Data Visualization

4.3 Challenges of Text Data Visualization

4.4 Various Forms of Text Data

4.5 Text Data Pre-processing Pipeline

4.6 Visualizing Text Data

4.7 Visualizing Conversations

Chapter 5 Visual Storytelling

5.1 Introduction

5.2 Why Storytelling Matters

5.3 Science behind Storytelling

5.4 Presentation Types

5.5 Death by Presentation

Chapter 6 Storytelling Framework

6.1 Introduction

6.2 Importance of Business Storytelling

6.3 Storytelling Frameworks

6.4 Data Storytelling

6.5 Narrative Types

6.6 Dimensions of Narrative Storytelling

6.7 Data Story Types

6.8 Analytics Dashboard

Chapter 7 Misleading with Charts

7.1 Introduction

7.2 Pre-attentive Processing of Visual Attributes

7.3 Types of Misleading Charts

7.4 More Examples of Misleading Visualization

Summary

Key Terms

Assignment Material

References