Prior knowledge of developing web applications is required. Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories, and key insights that are locked away. This learning path is divided into three modules. The first module will equip you with the key techniques required to overcome contemporary data visualization challenges.
After getting familiar with key concepts of data visualization, it's time to incorporate it with various technologies. This module provides a strong foundation in designing compelling web visualizations with D3.
By the end of this course, you will have unlocked the mystery behind successful data visualizations. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. We also do not have links that lead to sites DMCA copyright infringement. If You feel that this book is belong to you and you want to unpublish it, Please Contact us. Interactive Data Visualization 2nd Edition. Download e-Book. Posted on. Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and automatic computation to facilitate insight generation and knowledge crystallization from large and complex data.
The book provides a systematic and comprehensive overview of visual, interactive, and analytical methods. It introduces criteria for designing interactive visual data analysis solutions, discusses factors influencing the design, and examines the involved processes.
The reader is made familiar with the basics of visual encoding and gets to know numerous visualization techniques for multivariate data, temporal data, geo-spatial data, and graph data. A dedicated chapter introduces general concepts for interacting with visualizations and illustrates how modern interaction technology can facilitate the visual data analysis in many ways. The book also sheds light on advanced concepts for visualization in multi-display environments, user guidance during the data analysis, and progressive visual data analysis.
The authors present a top-down perspective on interactive visual data analysis with a focus on concise and clean terminology. Many real-world examples and rich illustrations make the book accessible to a broad interdisciplinary audience from students, to experts in the field, to practitioners in data-intensive application domains. Dataviz—the new language of business A good visualization can communicate the nature and potential impact of information and ideas more powerfully than any other form of communication.
No longer. A new generation of tools and massive amounts of available data make it easy for anyone to create visualizations that communicate ideas far more effectively than generic spreadsheet charts ever could. In Good Charts, dataviz maven Scott Berinato provides an essential guide to how visualization works and how to use this new language to impress and persuade.
Dataviz today is where spreadsheets and word processors were in the early s—on the cusp of changing how we work. Berinato lays out a system for thinking visually and building better charts through a process of talking, sketching, and prototyping. This book is much more than a set of static rules for making visualizations. Good Charts will help you turn plain, uninspiring charts that merely present information into smart, effective visualizations that powerfully convey ideas.
Data visualization is an efficient and effective medium for communicating large amounts of information, but the design process can often seem like an unexplainable creative endeavor. This concise book aims to demystify the design process by showing you how to use a linear decision-making process to encode your information visually.
Delve into different kinds of visualization, including infographics and visual art, and explore the influences at work in each one. Then learn how to apply these concepts to your design process. Learn data visualization classifications, including explanatory, exploratory, and hybrid Discover how three fundamental influences—the designer, the reader, and the data—shape what you create Learn how to describe the specific goal of your visualization and identify the supporting data Decide the spatial position of your visual entities with axes Encode the various dimensions of your data with appropriate visual properties, such as shape and color See visualization best practices and suggestions for encoding various specific data types.
If you are planning to create data analysis and visualization tools in the context of science, engineering, economics, or social science, then this book is for you. With this book, you will become a visualization expert, in a short time, using Mathematica. Practical data design tips from a data visualization expert ofthe modern age Data doesn? Thanks to the creative genius ofNathan Yau, we can. With this full-color book, data visualizationguru and author Nathan Yau uses step-by-step tutorials to show youhow to visualize and tell stories with data.
He explains how togather, parse, and format data and then design high qualitygraphics that help you explore and present patterns, outliers, andrelationships. Presents a unique approach to visualizing and telling storieswith data, from a data visualization expert and the creator offlowingdata.
Skip to content. Interactive Data Visualization for the Web. Interactive Data Visualization. Author : Matthew O. Interactive Data Visualization Book Review:. Interactive Visualization. Interactive Visualization Book Review:.
Hands On Data Visualization. Data Visualization. Data Visualization Book Review:. This book is designed as a textbook for students, researchers, analysts, professionals, and designers of visualization techniques, tools, and systems. It covers the full spectrum of the field, including mathematical and analytical aspects, ranging from its foundations to human visual perception; from coded algorithms for different types of data, information and tasks to the design and evaluation of new visualization techniques.
Numerous data sets have been made available that highlight different application areas and allow readers to evaluate the strengths and weaknesses of different visualization methods. Exercises, programming projects, and related readings are given for each chapter. The book concludes with an examination of several existing visualization systems and projections on the future of the field.
0コメント