A comprehensive yet quick guide to the best approaches to designing data visualizations, with real examples and illustrative diagrams. Whatever the desired outcome ensure success by following this expert design process. This book is for anyone who has responsibility for, or is interested in trying to find innovative and effective ways to visually analyze and communicate data. There is no skill, no knowledge and no role-based pre-requisites or expectations of anyone reading this book.
Visualizing the data is an essential part of any data analysis. Modern computing developments have led to big improvements in graphic capabilities and there are many new possibilities for data displays. This book gives an overview of modern data visualization methods, both in theory and practice. It details modern graphical tools such as mosaic plots, parallel coordinate plots, and linked views. Coverage also examines graphical methodology for particular areas of statistics, for example Bayesian analysis, genomic data and cluster analysis, as well software for graphics.
This issue delivers concrete suggestions for optimally using data visualization in evaluation, as well as suggestions for best practices in data visualization design. It focuses on specific quantitative and qualitative data visualization approaches that include data dashboards, graphic recording, and geographic information systems (GIS). Readers will get a step-by-step process for designing an effective data dashboard system for programs and organizations, and various suggestions to improve their utility. The next section illustrates the role that graphic recording can play in helping programs and evaluators understand and communicate the mission and impact that an intervention is having in a democratic and culturally competent way. The GIS section provides specific examples of how mapped data can be used to understand program implementation and effectiveness, and the influence that the environment has on these outcomes. Discusses best practices that inform and shape our data visualization design choices Highlights the best use of each tool/approach Provides suggestions for effective practice Discuss the strengths and limitations of each approach in evaluation practice This is the 140th volume of the Jossey-Bass quarterly report series New Directions for Evaluation, an official publication of the American Evaluation Association.
A Data Visualization Guide for Business Professionals
Author: Cole Nussbaumer Knaflic
Publisher: John Wiley & Sons
Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!
Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualizationAbout This Book* This unique guide teaches you how to visualize your cluttered, huge amounts of big data with ease* It is rich with ample options and solid use cases for big data visualization, and is a must-have book for your shelf* Improve your decision-making by visualizing your big data the right wayWho This Book Is ForThis book is for data analysts or those with a basic knowledge of big data analysis who want to learn big data visualization in order to make their analysis more useful. You need sufficient knowledge of big data platform tools such as Hadoop and also some experience with programming languages such as R. This book will be great for those who are familiar with conventional data visualizations and now want to widen their horizon by exploring big data visualizations.What you will learn* Understand how "basic analytics" is affected by big data* Deep dive into effective and efficient ways of visualizing big data* Get to know approaches (using various technologies) to address the challenges of visualizing big data* Comprehend the concepts and models used to visualize big data* Know how to visualize big data in real time and for different use cases* Understand how to integrate popular dashboard visualization tools such as Splunk and Tableau* Get to know the value and process of integrating visual big data with BI tools such as Tableau* Make sense of the visualization options for big data, based upon the most suited visualization techniques for big dataIn DetailWhen it comes to big data, regular data visualization tools with basic features become insufficient. This book covers the concepts and models used to visualize big data, with a focus on efficient visualizations to improve better decision making.This book works around big data visualizations and the challenges around visualizing big data and address characteristic challenges of visualizing like speed in accessing, understanding/adding context to, improving the quality of the data, displaying results, outliers, and so on. We focus on the most popular libraries to execute the tasks of big data visualization and explore "big data oriented" tools such as Hadoop and Tableau.We will show you how data changes with different variables and how to visualize data in real time and for different use cases with step-through topics such as: importing data to something like Hadoop, basic analytics, the work arounds to typical big data visualization challenges, and the most popular libraries that work with big data.The choice of visualizations depends on the most suited visualization techniques for big data, and we will show you the various options for big data visualizations based upon industry-proven techniques that are most suited for big data. You will then learn how to integrate popular visualization tools with graphing databases to see how huge amounts of certain data can be visualized. Finally, you will find out how to display the integration of visual big data with BI using Cognos BI.
Designing a complete visualization system involves many subtle decisions. When designing a complex, real-world visualization system, such decisions involve many types of constraints, such as performance, platform (in)dependence, available programming languages and styles, user-interface toolkits, input/output data format constraints, integration with third-party code, and more. Focusing on those techniques and methods with the broadest applicability across fields, the second edition of Data Visualization: Principles and Practice provides a streamlined introduction to various visualization techniques. The book illustrates a wide variety of applications of data visualizations, illustrating the range of problems that can be tackled by such methods, and emphasizes the strong connections between visualization and related disciplines such as imaging and computer graphics. It covers a wide range of sub-topics in data visualization: data representation; visualization of scalar, vector, tensor, and volumetric data; image processing and domain modeling techniques; and information visualization. See What’s New in the Second Edition: Additional visualization algorithms and techniques New examples of combined techniques for diffusion tensor imaging (DTI) visualization, illustrative fiber track rendering, and fiber bundling techniques Additional techniques for point-cloud reconstruction Additional advanced image segmentation algorithms Several important software systems and libraries Algorithmic and software design issues are illustrated throughout by (pseudo)code fragments written in the C++ programming language. Exercises covering the topics discussed in the book, as well as datasets and source code, are also provided as additional online resources.
A straightforward, full-color guide to showcasing data soyour audience can see what you mean, not just read about it Big data is big news! Every company, industry, not-for-profit,and government agency wants and needs to analyze and leveragedatasets that can quickly become ponderously large. Datavisualization software enables different industries to presentinformation in ways that are memorable and relevant to theirmission. This full-color guide introduces you to a variety of waysto handle and synthesize data in much more interesting ways thanmere columns and rows of numbers. Learn meaningful ways to show trending and relationships, how toconvey complex data in a clear, concise diagram, ways to createeye-catching visualizations, and much more! Effective data analysis involves learning how to synthesizedata, especially big data, into a story and present that story in away that resonates with the audience This full-color guide shows you how to analyze large amounts ofdata, communicate complex data in a meaningful way, and quicklyslice data into various views Explains how to automate redundant reporting and analyses,create eye-catching visualizations, and use statistical graphicsand thematic cartography Enables you to present vast amounts of data in ways that won'toverwhelm your audience Part technical manual and part analytical guidebook, DataVisualization For Dummies is the perfect tool for transformingdull tables and charts into high-impact visuals your audience willnotice...and remember.