"Mastering QlikView Data Visualization" is your essential guide to becoming proficient in advanced data visualization and analysis using QlikView. Through practical examples and real-world scenarios, this book enables you to create insightful and meaningful QlikView applications tailored to business needs. What this Book will help me do Design and implement advanced QlikView applications using realistic data and scenarios. Understand and fulfill business requirements across varied organizational departments. Create advanced charts and visualizations including frequency polygons and XmR charts. Integrate geographical, sentiment, and planning analysis into your QlikView models. Develop troubleshooting strategies for common QlikView data visualization challenges. Author(s) None Pover, an expert in data analytics and QlikView technologies, has extensive experience in implementing QlikView applications to address real-world business challenges. They are passionate about teaching practical solutions, ensuring readers gain actionable insights. With hands-on expertise, the author delivers clear, structured guidance in technical learning. Who is it for? If you're a QlikView developer wanting to go beyond the basics, this book is perfect for you. It is designed for individuals who have foundational knowledge of QlikView and are looking to enhance their ability to handle advanced projects. Whether you're focusing on analytics for sales, finance, or operations, you'll find this guide extremely useful.

In 'Python Data Visualization Cookbook (Second Edition)', you'll learn how to create stunning and meaningful visual representations of data using Python's powerful libraries. Through step-by-step, recipe-based guidance, this book equips you to transform raw data into comprehensible and compelling visual stories. What this Book will help me do Master setting up Python and its libraries for data visualization. Learn how to import, clean, and organize data effectively. Create a variety of plots and charts tailored to your data's needs. Explore 3D visualizations and animations for more complex data insights. Incorporate visualization into environments like LaTeX and web frameworks. Author(s) The authors Igor Milovanovic, None Foures, and Giuseppe Vettigli bring extensive experience in Python programming and data analysis. With a passion for teaching and a clear instructional style, they make complex topics approachable and engaging. Their expertise ensures you gain practical knowledge you can apply immediately. Who is it for? This book is perfect for Python programmers who want to deepen their understanding of data and learn how to visualize it effectively. It's suitable for readers with basic Python knowledge, looking to elevate their skills in data visualization. Whether you aim to improve at data-driven storytelling or analyze data in clarity, this book has you covered.

Unchain your data from the desktop with responsive visualizations Building Responsive Data Visualization for the Web is a handbook for any front-end development team needing a framework for integrating responsive web design into the current workflow. Written by a leading industry expert and design lead at Starbase Go, this book provides a wealth of information and practical guidance from the perspective of a real-world designer. You'll walk through the process of building data visualizations responsively as you learn best practices that build upon responsive web design principles, and get the hands-on practice you need with exercises, examples, and source code provided in every chapter. These strategies are designed to be implemented by teams large and small, with varying skill sets, so you can apply these concepts and skills to your project right away. Responsive web design is the practice of building a website to suit base browser capability, then adding features that enhance the experience based on the user's device's capabilities. Applying these ideas to data produces visualizations that always look as if they were designed specifically for the device through which they are viewed. This book shows you how to incorporate these principles into your current practices, with highly practical hands-on training. Examine the hard data surrounding responsive design Master best practices with hands-on exercises Learn data-based document manipulation using D3.js Adapt your current strategies to responsive workflows Data is growing exponentially, and the need to visualize it in any context has become crucial. Traditional visualizations allow important data to become lost when viewed on a small screen, and the web traffic speaks for itself – viewers repeatedly demonstrate their preference for responsive design. If you're ready to create more accessible, take-anywhere visualizations, Building Responsive Data Visualization for the Web is your tailor-made solution.

Mastering Python Data Visualization provides thorough, hands-on guidance for creating impactful visual representations of data by leveraging Python's powerful libraries such as Matplotlib, Pandas, and Scikit-Learn. By following this book, you will gain proficiency in understanding data, performing analyses, and ultimately presenting your findings in a clear and engaging way. What this Book will help me do Effectively transform raw data into insightful visualizations using Python's rich ecosystem of libraries. Understand and apply best practices for selecting the most appropriate visualization techniques for different datasets and objectives. Master the use of Python for interactive plotting, regression analysis, clustering, and classification tasks. Develop a solid foundation in data visualization aesthetics and how to convey information clearly through visuals. Utilize Python for specialized fields such as finance, bioinformatics, and social network analysis, incorporating advanced computation techniques. Author(s) Kirthi Raman is an experienced data scientist and Python advocate with a strong background in technical computing and data visualization. He has hands-on experience in using Python's ecosystem to solve real-world data problems and a passion for sharing knowledge. Raman's writing focuses on blending practical insights with comprehensive explanations, ensuring readers not only learn the tools but also apply them effectively. Who is it for? This book is ideal for data analysts, data scientists, and researchers who want to deepen their knowledge of Python-based data visualization techniques. It requires readers to have a basic understanding of Python and data manipulation. If your goal is to create professional and informative visual narratives that are both visually appealing and data-driven, this book is for you.

SAS Programming and Data Visualization Techniques: A Power User’s Guide brings together a wealth of ideas about strategic and tactical solutions to everyday situations experienced when transferring, extracting, processing, analyzing, and reporting the valuable data you have at your fingertips. Best, you can achieve most of the solutions using the SAS components you already license, meaning that this book’s insights can keep you from throwing money at problems needlessly. Author Philip R. Holland advises a broad range of clients throughout Europe and the United States as an independent consultant and founder of Holland Numerics Ltd, a SAS technical consultancy. In this book he explains techniques—through code samples and example—that will enable you to increase your knowledge of all aspects of SAS programming, improve your coding productivity, and interface SAS with other programs. He also provides an expert’s overview of Graph Templates, which was recently moved into Base SAS. You will learn to create attractive, standardized, reusable, and platform-independent graphs—both statistical and non-statistical—to help you and your business users explore, visualize, and capitalize on your company’s data. In addition, you will find many examples and cases pertaining to healthcare, finance, retail, and other industries. Among other things, SAS Programming and Data Visualization Techniques will show you how to: Write efficient and reusable SAS code Combine look-up data sets with larger data sets effectively Run R and Perl from SAS Run SAS programs from SAS Studio and Enterprise Guide Output data into insightful, valuable charts and graphs SAS Programming and Data Visualization Techniques prepares you to make better use of your existing SAS components by learning to use the newest features, improve your coding efficiency, help you develop applications that are easier to maintain, and make data analysis easier. In other words, it will save you time, money, and effort—and make you a more valuable member of the development team.

In "Data Visualization with D3 and AngularJS," you'll discover how to create dynamic, data-driven visualizations with the power of D3.js integrated seamlessly into AngularJS apps. This book offers a hands-on approach, demonstrating step-by-step how to leverage the strengths of these technologies to build interactive dashboards and visual components. What this Book will help me do Build and integrate interactive dashboards using D3.js and AngularJS. Design varied types of charts, including scatter plots, bar graphs, and area charts. Understand how to load, parse, and preprocess external data for visualizations. Develop modular and reusable visualization components in AngularJS. Create custom animations and interactions for user engagement with data visualizations. Author(s) With years of experience in front-end development and data visualization, the authors None Hanchett and None Körner bring expert insight and clarity to these topics. Their instructional approach focuses on practical, real-world applications, aiming to empower readers to achieve professional results through clear explanations and well-structured examples. Who is it for? This book is tailored for web developers familiar with AngularJS who are eager to incorporate advanced visualizations into their applications. Whether you're looking to build professional dashboards or simply explore the capabilities of D3.js, this book provides the knowledge you need. Ideal for those aiming to gain hands-on experience and enhance their development skill set.

The only Oracle Press guide to creating effective visual presentations of business intelligence data quickly and easily Data Visualization for Oracle Business Intelligence 11g reveals the best practices for creating graphs, tables, maps, and other methodologies for presenting data-driven insights using one of the most common business intelligence front-end systems in the world, Oracle Business Intelligence 11 g. This information-rich guide offers clear instructions for building top-quality dashboards, analyses, and visualizations from real-world implementers and respected data visualization experts. You’ll learn everything from improving the readability of your tables to implementing the latest Advanced Trellis Chart features and from adding native map views of BI data to designing optimal dashboard layout strategies. You’ll see how to produce accurate, compelling, and professional graphics that will immediately enhance corporate decision making. Shows proven steps for extracting maximum impact from native features that are little known to the majority of BI users Covers dashboard strategy, including layout, design, navigation, master detail linking, action links, and prompts Addresses how to extend Oracle Business Intelligence 11 g with advanced languages and visualization systems such as JavaScript-based D3 and JQuery, R, and Oracle Application Development Framework Includes an associated web gallery showcasing the colors and graphics that render best digitally

Wring more out of the data with a scientific approach to analysis Graph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations using a rich and engaging set of examples from sports, finance, marketing, security, social media, and more. You will find practical guidance toward pattern identification and using various data sources, including Big Data, plus clear instruction on the use of software and programming. The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book. Science has already reaped the benefit of network and graph theory, which has powered breakthroughs in physics, economics, genetics, and more. This book brings those proven techniques into the world of business, finance, strategy, and design, helping extract more information from data and better communicate the results to decision-makers. Study graphical examples of networks using clear and insightful visualizations Analyze specifically-curated, easy-to-use data sets from various industries Learn the software tools and programming languages that extract insights from data Code examples using the popular Python programming language There is a tremendous body of scientific work on network and graph theory, but very little of it directly applies to analyst functions outside of the core sciences - until now. Written for those seeking empirically based, systematic analysis methods and powerful tools that apply outside the lab, Graph Analysis and Visualization is a thorough, authoritative resource.

This book provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices. It features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques for spatial data, and visual analytics techniques for interweaving data transformation and analysis with interactive visual exploration. Suitable for both beginners and more experienced designers, the book does not assume any experience with programming, mathematics, human-computer interaction, or graphic design.

This book explores the study of processing and visually representing data sets. Data visualization is closely related to information graphics, information visualization, scientific visualization, and statistical graphics. This second edition presents a better treatment of the relationship between traditional scientific visualization and information visualization, a description of the emerging field of visual analytics, and updated techniques using the GPU and new generations of software tools and packages. This edition is also enhanced with exercises and downloadable code and data sets.

Master D3, Today’s Most Powerful Tool for Visualizing Data on the Web Data-driven graphics are everywhere these days, from websites and mobile apps to interactive journalism and high-end presentations. Using D3, you can create graphics that are visually stunning and powerfully effective. is a hands-on, full-color tutorial that teaches you to design charts and data visualizations to tell your story quickly and intuitively, and that shows you how to wield the powerful D3 JavaScript library. Visual Storytelling with D3 Drawing on his extensive experience as a professional graphic artist, writer, and programmer, Ritchie S. King walks you through a complete sample project—from conception through data selection and design. Step by step, you’ll build your skills, mastering increasingly sophisticated graphical forms and techniques. If you know a little HTML and CSS, you have all the technical background you’ll need to master D3. This tutorial is for web designers creating graphics-driven sites, services, tools, or dashboards; online journalists who want to visualize their content; researchers seeking to communicate their results more intuitively; marketers aiming to deepen their connections with customers; and for any data visualization enthusiast. Coverage includes Identifying a data-driven story and telling it visually Creating and manipulating beautiful graphical elements with SVG Shaping web pages with D3 Structuring data so D3 can easily visualize it Using D3’s data joins to connect your data to the graphical elements on a web page Sizing and scaling charts, and adding axes to them Loading and filtering data from external standalone datasets Animating your charts with D3’s transitions Adding interactivity to visualizations, including a play button that cycles through different views of your data Finding D3 resources and getting involved in the thriving online D3 community About the Website All of this book’s examples are available at ritchiesking.com/book, along with video tutorials, updates, supporting material, and even more examples, as they become available.

Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner. The book includes: A deep discussion of streaming data systems and architectures Instructions for analyzing, storing, and delivering streaming data Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies for website analytics, Big Data, visualizing streaming and mobile data, and mining and visualizing operational data flows. The book's "recipe" layout lets readers quickly learn and implement different techniques. All of the code examples presented in the book, along with their related data sets, are available on the companion website.

High Impact Data Visualization with Power View, Power Map, and Power BI helps you take business intelligence delivery to a new level that is interactive, engaging, even fun, all while driving commercial success through sound decision-making. Learn to harness the power of Microsoft’s flagship, self-service business intelligence suite to deliver compelling and interactive insight with remarkable ease. Learn the essential techniques needed to enhance the look and feel of reports and dashboards so that you can seize your audience’s attention and provide them with clear and accurate information. Also learn to integrate data from a variety of sources and create coherent data models displaying clear metrics and attributes. Power View is Microsoft's ground-breaking tool for ad-hoc data visualization and analysis. It's designed to produce elegant and visually arresting output. It's also built to enhance user experience through polished interactivity. Power Map is a similarly powerful mechanism for analyzing data across geographic and political units. Power Query lets you load, shape and streamline data from multiple sources. PowerPivot can extend and develop data into a dynamic model. Power BI allows you to share your findings with colleagues, and present your insights to clients. High Impact Data Visualization with Power View, Power Map, and Power BI helps you master this suite of powerful tools from Microsoft. You'll learn to identify data sources, and to save time by preparing your underlying data correctly. You'll also learn to deliver your powerful visualizations and analyses through the cloud to PCs, tablets and smartphones. Simple techniques take raw data and convert it into information. Slicing and dicing metrics delivers interactive insight. Visually arresting output grabs and focuses attention on key indicators.

The era of Big Data as arrived, and most organizations are woefully unprepared. Slowly, many are discovering that stalwarts like Excel spreadsheets, KPIs, standard reports, and even traditional business intelligence tools aren't sufficient. These old standbys can't begin to handle today's increasing streams, volumes, and types of data. Amidst all of the chaos, though, a new type of organization is emerging. In The Visual Organization, award-winning author and technology expert Phil Simon looks at how an increasingly number of organizations are embracing new dataviz tools and, more important, a new mind-set based upon data discovery and exploration. Simon adroitly shows how Amazon, Apple, Facebook, Google, Twitter, and other tech heavyweights use powerful data visualization tools to garner fascinating insights into their businesses. But make no mistake: these companies are hardly alone. Organizations of all types, industries, sizes are representing their data in new and amazing ways. As a result, they are asking better questions and making better business decisions. Rife with real-world examples and case studies, The Visual Organization is a full-color tour-de-force.

A straightforward, full-color guide to showcasing data so your 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 leverage datasets that can quickly become ponderously large. Data visualization software enables different industries to present information in ways that are memorable and relevant to their mission. This full-color guide introduces you to a variety of ways to handle and synthesize data in much more interesting ways than mere columns and rows of numbers. Learn meaningful ways to show trending and relationships, how to convey complex data in a clear, concise diagram, ways to create eye-catching visualizations, and much more! Effective data analysis involves learning how to synthesize data, especially big data, into a story and present that story in a way that resonates with the audience This full-color guide shows you how to analyze large amounts of data, communicate complex data in a meaningful way, and quickly slice data into various views Explains how to automate redundant reporting and analyses, create eye-catching visualizations, and use statistical graphics and thematic cartography Enables you to present vast amounts of data in ways that won't overwhelm your audience Part technical manual and part analytical guidebook, Data Visualization For Dummies is the perfect tool for transforming dull tables and charts into high-impact visuals your audience will notice...and remember.

Best practices and step-by-step instructions for using the Tableau Software toolset Although the Tableau Desktop interface is relatively intuitive, this book goes beyond the simple mechanics of the interface to show best practices for creating effective visualizations for specific business intelligence objectives. It illustrates little-known features and techniques for getting the most from the Tableau toolset, supporting the needs of the business analysts who use the product as well as the data and IT managers who support it. This comprehensive guide covers the core feature set for data analytics, illustrating best practices for creating and sharing specific types of dynamic data visualizations. Featuring a helpful full-color layout, the book covers analyzing data with Tableau Desktop, sharing information with Tableau Server, understanding Tableau functions and calculations, and Use Cases for Tableau Software. Includes little-known, as well as more advanced features and techniques, using detailed, real-world case studies that the author has developed as part of his consulting and training practice Explains why and how Tableau differs from traditional business information analysis tools Shows you how to deploy dashboards and visualizations throughout the enterprise Provides a detailed reference resource that is aimed at users of all skill levels Depicts ways to leverage Tableau across the value chain in the enterprise through case studies that target common business requirements Endorsed by Tableau Software Tableau Your Data shows you how to build dynamic, best-of-breed visualizations using the Tableau Software toolset.

Dive into the world of data visualization with 'Data Visualization with D3.js Cookbook'. This book provides a hands-on approach to mastering data visualization using D3.js, a powerful JavaScript library that brings data to life using HTML, SVG, and CSS. Through step-by-step recipes, you'll learn everything you need to create stunning, interactive, and effective visualizations. What this Book will help me do Develop expertise in functional JavaScript to create elegant D3 visualizations. Learn to work with HTML and SVG elements efficiently to design effective visuals. Master the use of D3 scales and interpolators to represent data accurately. Enhance your understanding of D3 layouts and force-directed visuals for complex data. Create interactive and responsive visualizations for web applications. Author(s) Nick Zhu is an experienced software engineer and data visualization enthusiast with extensive expertise in JavaScript and web development. Authoring 'Data Visualization with D3.js Cookbook', Nick adeptly shares his knowledge, making complex topics approachable. His passion for clear communication shines in his instructive writing style. Who is it for? This book is designed for developers who have some knowledge of HTML, CSS, and JavaScript and aim to excel in data visualization using D3.js. If you strive for deeper mastery of D3 and wish to enhance your ability to create compelling graphics, this book is ideal for you. It serves both as a learning resource for newcomers and a quick reference for experienced practitioners. Your goal to transform data into impactful visuals aligns perfectly with the insights offered.

Pro Data Visualization using R and JavaScript makes the R language approachable, and promotes the idea of data gathering and analysis. You'll see how to use R to interrogate and analyze your data, and then use the D3 JavaScript library to format and display that data in an elegant, informative, and interactive way. You will learn how to gather data effectively, and also how to understand the philosophy and implementation of each type of chart, so as to be able to represent the results visually. With the popularity of the R language, the art and practice of creating data visualizations is no longer the preserve of mathematicians, statisticians, or cartographers. As technology leaders, we can gather metrics around what we do and use data visualizations to communicate that information. Pro Data Visualization using R and JavaScript combines the power of the R language with the simplicity and familiarity of JavaScript to display clear and informative data visualizations. Gathering and analyzing empirical data is the key to truly understanding anything. We can track operational metrics to quantify the health of our products in production. We can track quality metrics of our projects, and even use our data to identify bad code. Visualizing this data allows anyone to read our analysis and easily get a deep understanding of the story the data tells. What you'll learn A rich understanding of how to gather, and analyze empirical data How to tell a story with data using data visualizations What types of data visualizations are best to use for the story that you want to tell with your data A comprehensive introduction to the R language, covering all the essentials Exploration of how to construct interactive data visualizations using JavaScript and JavaScript libraries Who this book is for Developers at all levels interested in data visualization, beginning to intermediate engineering managers, statisticians, mathematicians, economists and any others interested in data visualization.

Go beyond design concepts and learn to build state-of-the-art visualizations The visualization experts at Microsoft's Pragmatic Works have created a full-color, step-by-step guide to building specific types of visualizations. The book thoroughly covers the Microsoft toolset for data analysis and visualization, including Excel, and explores best practices for choosing a data visualization design, selecting tools from the Microsoft stack, and building a dynamic data visualization from start to finish. You'll examine different types of visualizations, their strengths and weaknesses, and when to use each one. Data visualization tools unlock the stories within the data, enabling you to present it in a way that is useful for making business decisions This full-color guide introduces data visualization design concepts, then explains the various Microsoft tools used to store and display data Features a detailed discussion of various classes of visualizations, their uses, and the appropriate tools for each Includes practical implementations of various visualizations and best practices for using them Covers out-of-the-box Microsoft tools, custom-developed illustrations and implementations, and code examples Visual Intelligence: Microsoft Tools and Techniques for Visualizing Data arms you with best practices and the knowledge to choose and build dynamic data visualizations.

A fresh look at visualization from the author of Visualize This Whether it's statistical charts, geographic maps, or the snappy graphical statistics you see on your favorite news sites, the art of data graphics or visualization is fast becoming a movement of its own. In Data Points: Visualization That Means Something, author Nathan Yau presents an intriguing complement to his bestseller Visualize This, this time focusing on the graphics side of data analysis. Using examples from art, design, business, statistics, cartography, and online media, he explores both standard-and not so standard-concepts and ideas about illustrating data. Shares intriguing ideas from Nathan Yau, author of Visualize This and creator of flowingdata.com, with over 66,000 subscribers Focuses on visualization, data graphics that help viewers see trends and patterns they might not otherwise see in a table Includes examples from the author's own illustrations, as well as 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 Data Points: Visualization That Means Something.

Create and publish your own interactive data visualization projects on the Web—even if you have little or no experience with data visualization or web development. It’s easy and fun with this practical, hands-on introduction. Author Scott Murray teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser. Along the way, you’ll expand your web programming skills, using tools such as HTML and JavaScript. This step-by-step guide is ideal whether you’re a designer or visual artist with no programming experience, a reporter exploring the new frontier of data journalism, or anyone who wants to visualize and share data. Learn HTML, CSS, JavaScript, and SVG basics Dynamically generate web page elements from your data—and choose visual encoding rules to style them Create bar charts, scatter plots, pie charts, stacked bar charts, and force-directed layouts Use smooth, animated transitions to show changes in your data Introduce interactivity to help users explore data through different views Create customized geographic maps with data Explore hands-on with downloadable code and over 100 examples

Dive into the world of data visualization with 'Data Visualization: a Successful Design Process'. Learn to convert complex datasets into vivid, insightful visuals using proven design methodologies and tools. This resource equips you to craft visuals that not only engage your audience but also uncover critical trends and narratives hidden in data. What this Book will help me do Master the fundamentals of visualization taxonomy to choose the ideal design for your data. Develop analytical questions and identify key narratives to structure your data representation. Understand the human visual system and how it impacts effective visual communication. Apply critical thinking to select visualization techniques suited to different data types. Gain an in-depth knowledge of data visualization tools and contemporary practices. Author(s) The author of this book is a seasoned expert in the field of data visualization, known for their innovative approach to transforming data into impactful visuals. With years of experience navigating the intersection of data science and design, their method focuses on empowering professionals to communicate insights effectively. Their writing combines a deep understanding of technical skills with actionable, inspiring guidance. Who is it for? This book is perfect for professionals, analysts, and designers who aim to improve their data visualization skills. Whether you are a beginner or an experienced individual seeking to refine your approach, this book caters to all skill levels. If your goal includes communicating data insights clearly and effectively to varied audiences, this book is for you.

Reveals how to build rich BI reports with just a few clicks using Crescent, Microsoft’s newest BI tool Technical review by Microsoft’s Crescent team and Foreword by Group Program Manager for Crescent Complete, practical examples are immediately usable to readers in a commercial environment CD-ROM contains 30+ reusable reports, all code samples, and supporting animations that walk thru each example

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

A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences. Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis: Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces. Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed. Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naïve Bayes. Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios. Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series ( www.makingsenseofdata.com) provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online. With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization.