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Название: Data Visualization Made Simple: Insights into Becoming Visual
Автор: Kristen Sosulski
Издательство: Routledge
ISBN: 1138503916
Год: 2018
Страниц: 284
Язык: английский
Формат: pdf (true)
Размер: 33.0 MB

Data Visualization Made Simple is a practical guide to the fundamentals, strategies, and real-world cases for data visualization, an essential skill required in today’s information-rich world. With foundations rooted in statistics, psychology, and computer science, data visualization offers practitioners in almost every field a coherent way to share findings from original research, big data, learning analytics, and more.

In nine appealing chapters, the book:

- examines the role of data graphics in decision-making, sharing information, sparking discussions, and inspiring future research;
- scrutinizes data graphics, deliberates on the messages they convey, and looks at options for design visualization; and
- includes cases and interviews to provide a contemporary view of how data graphics are used by professionals across industries

Both novices and seasoned designers in education, business, and other areas can use this book’s effective, linear process to develop data visualization literacy and promote exploratory, inquiry-based approaches to visualization problems

Data visualization software applications are ubiquitous. These applications focus on usability through a drag and drop interface. They are designed for everyone from novices to expert visualization designers and analysts. Tableau Desktop and many other specialized data visualization software packages (e.g., QlikView, Domo, ArcGIS, IBM Watson Analytics, SAS, Microsoft’s Power BI) offer an interface for visualizing data. These applications offer a full-range of data graphics from basic charts to maps. These tools feature Interactive, static, animated, multiple-dimensional linked charts, and dashboard displays.

For developers, analysts, and designers who want to visualize data in their own programming environment, there are several contenders. Most programming languages have data graphic packages. Python and R have a sophisticated set of libraries or packages for data visualization. In addition, there are numerous javascript libraries for web-based data graphics.

Contents:


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