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The Visual Imperative - 1st Edition - ISBN: 9780128038444, 9780128039304

The Visual Imperative

1st Edition

Creating a Visual Culture of Data Discovery

Author: Lindy Ryan
Paperback ISBN: 9780128038444
eBook ISBN: 9780128039304
Imprint: Morgan Kaufmann
Published Date: 9th March 2016
Page Count: 320
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Data is powerful. It separates leaders from laggards and it drives business disruption, transformation, and reinvention. Today’s most progressive companies are using the power of data to propel their industries into new areas of innovation, specialization, and optimization. The horsepower of new tools and technologies have provided more opportunities than ever to harness, integrate, and interact with massive amounts of disparate data for business insights and value – something that will only continue in the era of the Internet of Things. And, as a new breed of tech-savvy and digitally native knowledge workers rise to the ranks of data scientist and visual analyst, the needs and demands of the people working with data are changing, too.

The world of data is changing fast. And, it’s becoming more visual.

Visual insights are becoming increasingly dominant in information management, and with the reinvigorated role of data visualization, this imperative is a driving force to creating a visual culture of data discovery. The traditional standards of data visualizations are making way for richer, more robust and more advanced visualizations and new ways of seeing and interacting with data. However, while data visualization is a critical tool to exploring and understanding bigger and more diverse and dynamic data, by understanding and embracing our human hardwiring for visual communication and storytelling and properly incorporating key design principles and evolving best practices, we take the next step forward to transform data visualizations from tools into unique visual information assets.

Key Features

  • Discusses several years of in-depth industry research and presents vendor tools, approaches, and methodologies in discovery, visualization, and visual analytics
  • Provides practicable and use case-based experience from advisory work with Fortune 100 and 500 companies across multiple verticals
  • Presents the next-generation of visual discovery, data storytelling, and the Five Steps to Data Storytelling with Visualization
  • Explains the Convergence of Visual Analytics and Visual discovery, including how to use tools such as R in statistical and analytic modeling
  • Covers emerging technologies such as streaming visualization in the IOT (Internet of Things) and streaming animation


Data analysts, data scientists, data architects. Data science Researchers in academia.

Table of Contents

1. Separating Leaders from Laggards
2. Improved Agility and Insights through Visual Discovery
3. From Self-Service to Self-Sufficiency
4. Navigating Ethics in the Big Data Democracy
5. Data Science Education and Leadership Landscape
6. Visual Communication and Literacy
7. Visual Data Storytelling
8. The Importance of Visual Design
9. The Data Viz Continuum: Exploratory, Explanatory, Infographics, & Iconography
10. Architecting for Discovery
11. Data Visualization as a Core Competency
12. Enabling Visual Data Discovery by Design
13. Visualization in the Internet of Things


No. of pages:
© Morgan Kaufmann 2016
9th March 2016
Morgan Kaufmann
Paperback ISBN:
eBook ISBN:

About the Author

Lindy Ryan

Lindy Ryan is a respected analyst and researcher in the confluence of data discovery, visualization, and data science. Her dissertation research focuses on addressing the technical, ethical, and cultural impacts that have already and will continue to arise in a rapidly expanding big data culture. She is a regular contributor to several industry publications, as well as a frequent guest speaker at data conferences worldwide.

Affiliations and Expertise

Research Director, Data Discovery and Visualization, Radiant Advisors Research Associate, Rutgers University’s Discovery Informatics Institute (RDI2) Associate Faculty, City University of Seattle

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