Data Points

Author: Nathan Yau
Editor: John Wiley & Sons
ISBN: 1118654935
Size: 17,78 MB
Format: PDF, Kindle
Read: 692
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A fresh look at visualization from the author of VisualizeThis Whether it's statistical charts, geographic maps, or the snappygraphical statistics you see on your favorite news sites, the artof data graphics or visualization is fast becoming a movement ofits own. In Data Points: Visualization That Means Something,author Nathan Yau presents an intriguing complement to hisbestseller Visualize This, this time focusing on thegraphics side of data analysis. Using examples from art, design,business, statistics, cartography, and online media, he exploresboth standard-and not so standard-concepts and ideas aboutillustrating data. Shares intriguing ideas from Nathan Yau, author of VisualizeThis and creator of flowingdata.com, with over 66,000subscribers Focuses on visualization, data graphics that help viewers seetrends and patterns they might not otherwise see in a table Includes examples from the author's own illustrations, as wellas from professionals in statistics, art, design, business,computer science, cartography, and more Examines standard rules across all visualization applications,then explores when and where you can break those rules Create visualizations that register at all levels, with DataPoints: Visualization That Means Something.

Data Driven Security

Author: Jay Jacobs
Editor: John Wiley & Sons
ISBN: 111879382X
Size: 13,49 MB
Format: PDF
Read: 607
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Uncover hidden patterns of data and respond withcountermeasures Security professionals need all the tools at their disposal toincrease their visibility in order to prevent security breaches andattacks. This careful guide explores two of the most powerful data analysis and visualization. You'll soon understand how toharness and wield data, from collection and storage to managementand analysis as well as visualization and presentation. Using ahands-on approach with real-world examples, this book shows you howto gather feedback, measure the effectiveness of your securitymethods, and make better decisions. Everything in this book will have practical application forinformation security professionals. Helps IT and security professionals understand and use data, sothey can thwart attacks and understand and visualizevulnerabilities in their networks Includes more than a dozen real-world examples and hands-onexercises that demonstrate how to analyze security data andintelligence and translate that information into visualizationsthat make plain how to prevent attacks Covers topics such as how to acquire and prepare security data,use simple statistical methods to detect malware, predict roguebehavior, correlate security events, and more Written by a team of well-known experts in the field ofsecurity and data analysis Lock down your networks, prevent hacks, and thwart malware byimproving visibility into the environment, all through the power ofdata and Security Using Data Analysis, Visualization, andDashboards.

The New Abcs Of Research

Author: Ben Shneiderman
Editor: Oxford University Press
ISBN: 0198758839
Size: 16,17 MB
Format: PDF, ePub
Read: 517
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The problems we face in the 21st century require innovative thinking from all of us. Be it students, academics, business researchers of government policy makers. Hopes for improving our healthcare, food supply, community safety and environmental sustainability depend on the pervasive application of research solutions. The research heroes who take on the immense problems of our time face bigger than ever challenges, but if they adopt potent guiding principles and effective research lifecycle strategies, they can produce the advances that will enhance the lives of many people. These inspirational research leaders will break free from traditional thinking, disciplinary boundaries, and narrow aspirations. They will be bold innovators and engaged collaborators, who are ready to lead, yet open to new ideas, self-confident, yet empathetic to others. In this book, Ben Shneiderman recognizes the unbounded nature of human creativity, the multiplicative power of teamwork, and the catalytic effects of innovation. He reports on the growing number of initiatives to promote more integrated approaches to research so as to promote the expansion of these efforts. It is meant as a guide to students and junior researchers, as well as a manifesto for senior researchers and policy makers, challenging widely-held beliefs about how applied innovations evolve and how basic breakthroughs are made, and to help plotting the course towards tomorrow's great advancements.

Data Visualizations And Infographics

Author: Sarah K. C. Mauldin
Editor: Rowman & Littlefield
ISBN: 1442243880
Size: 18,40 MB
Format: PDF, ePub, Mobi
Read: 228
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This complete how-to guidebook provides you with the tools and inspiration you need to use infographics and data visualization techniques in your library to knock your audience’s socks off as you tell your story in a visual format that can be consumed and understood at a glance.

Data Visualization Made Simple

Author: Kristen Sosulski
Editor: Routledge
ISBN: 135138077X
Size: 12,48 MB
Format: PDF, Kindle
Read: 743
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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

Author: Lauren Magnuson
Editor: Rowman & Littlefield
ISBN: 1442271124
Size: 20,91 MB
Format: PDF, ePub, Mobi
Read: 953
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Data Visualization: A Guide to Visual Storytelling for Libraries is a practical guide to the skills and tools needed to create beautiful and meaningful visual stories through data visualization. Learn how to sift through complex datasets to better understand a variety of metrics, such as trends in user behavior and electronic resource usage, return on investment (ROI) and impact metrics, and data about library collections and repositories. A 20-page color insert showcases an extensive selection of visualizations using a variety of technologies and programming languages that can serve as inspiration for creating your own visualizations. Understanding and communicating trends from your organization’s data is essential. Whether you are looking to make more informed decisions by visualizing organizational data, or to tell the story of your library’s impact on your community, this book will give you the tools to make it happen.

R Data Visualization Cookbook

Author: Atmajitsinh Gohil
Editor: Packt Publishing Ltd
ISBN: 1783989513
Size: 10,21 MB
Format: PDF, ePub
Read: 597
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If you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this book is for you. Basic knowledge of R programming is expected.

Web And Network Data Science

Author: Thomas W. Miller
Editor: FT Press
ISBN: 0133887642
Size: 10,51 MB
Format: PDF
Read: 477
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Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.

Modeling Techniques In Predictive Analytics With Python And R

Author: Thomas W. Miller
Editor: FT Press
ISBN: 013389214X
Size: 20,18 MB
Format: PDF, Docs
Read: 762
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Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Modeling Techniques In Predictive Analytics

Author: Thomas W. Miller
Editor: FT Press
ISBN: 0133886190
Size: 10,88 MB
Format: PDF, ePub, Docs
Read: 501
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To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more