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| business analytics and data visualization: Storytelling with Data Cole Nussbaumer Knaflic, 2015-10-09 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! |
| business analytics and data visualization: Graph Analysis and Visualization Richard Brath, David Jonker, 2015-01-30 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. |
| business analytics and data visualization: Business Analytics, Volume I Amar Sahay, 2018-08-23 Business Analytics: A Data-Driven Decision Making Approach for Business-Part I,/i> provides an overview of business analytics (BA), business intelligence (BI), and the role and importance of these in the modern business decision-making. The book discusses all these areas along with three main analytics categories: (1) descriptive, (2) predictive, and (3) prescriptive analytics with their tools and applications in business. This volume focuses on descriptive analytics that involves the use of descriptive and visual or graphical methods, numerical methods, as well as data analysis tools, big data applications, and the use of data dashboards to understand business performance. The highlights of this volume are: Business analytics at a glance; Business intelligence (BI), data analytics; Data, data types, descriptive analytics; Data visualization tools; Data visualization with big data; Descriptive analytics-numerical methods; Case analysis with computer applications. |
| business analytics and data visualization: Learning Tableau Joshua N. Milligan, 2015-04-27 If you want to understand your data using data visualization and don't know where to start, then this is the book for you. Whether you are a beginner or have years of experience, this book will help you to quickly acquire the skills and techniques used to discover, analyze, and communicate data visually. Some familiarity with databases and data structures is helpful, but not required. |
| business analytics and data visualization: The Big Picture: How to Use Data Visualization to Make Better Decisions—Faster Steve Wexler, 2021-05-18 Not a data expert? Here’s an engaging and entertaining guide to interpreting and drawing insights from any chart, graph, or other data visualization you’ll encounter. You’re a business professional, not a data scientist. How do you make heads or tails of the data visualizations that come across your desk—let alone make critical business decisions based on the information they’re designed to convey? In The Big Picture, top data visualization consultant Steve Wexler provides the tools for developing the graphical literacy you need to understand the data visualizations that are flooding your inbox—and put that data to use. Packed with the best four-color examples created in Excel, Tableau, Power BI, and Qlik, among others, this one-stop resource empowers you to extract the most important information from data visualizations quickly and accurately, act on key insights, solve problems, and make the right decisions for your organization every time. |
| business analytics and data visualization: Data Analysis for Business, Economics, and Policy Gábor Békés, Gábor Kézdi, 2021-05-06 A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data. |
| business analytics and data visualization: Data Points Nathan Yau, 2013-03-25 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. |
| business analytics and data visualization: Learning Tableau 10 Joshua N. Milligan, 2016-09-30 Learn how to create effective data visualizations with Tableau and unlock a smarter approach to business analytics. It might just transform your organization About This Book Create stylish visualizations and dashboards that explain complexity with clarity Learn effective data storytelling to transform how your business uses ideas and makes decisions Explore all the new features in Tableau 10 and start to redefine what business analytics means to your organization Who This Book Is For Got data? Not sure what to make of it? This is the guide for you – whether you've been working with Tableau for years or are just beginning your adventure into business analytics. What You Will Learn Find out how to build effective visualizations and dashboards Prepare and clean your data so you can be sure Tableau is finding answers to your questions – not raising more problems Discover how to create advanced visualizations that explain complexity with clarity and style Dig deeper into your data with clustering and distribution models that allow you to analyze trends and make forecasts Learn how to use data storytelling to aid decision-making and strategy Share dashboards and visualizations to cultivate a culture where data is available and valued In Detail Tableau has for some time been one of the most popular Business Intelligence and data visualization tools available. Why? Because, quite simply, it's a tool that's responsive to the needs of modern businesses. But it's most effective when you know how to get what you want from it – it might make your business intelligent, but it isn't going to make you intelligent... We'll make sure you're well prepared to take full advantage of Tableau 10's new features. Whether you're an experienced data analyst that wants to explore 2016's new Tableau, or you're a beginner that wants to expand their skillset and bring a more professional and sharper approach to their organization, we've got you covered. Beginning with the fundamentals, such as data preparation, you'll soon learn how to build and customize your own data visualizations and dashboards, essential for high-level visibility and effective data storytelling. You'll also find out how to so trend analysis and forecasting using clustering and distribution models to inform your analytics. But it's not just about you – when it comes to data it's all about availability and access. That's why we'll show you how to share your Tableau visualizations. It's only once insights are shared and communicated that you – and your organization – will start making smarter and informed decisions. And really, that's exactly what this guide is for. Style and approach Practical yet comprehensive, this Tableau guide takes you from the fundamentals of the tool before diving deeper into creating advanced visualizations. Covering the latest features found in Tableau 10, this might be the guide that transforms your organization. |
| business analytics and data visualization: Business Analytics S. Christian Albright, Wayne L. Winston, 2017 |
| business analytics and data visualization: Data Analytics & Visualization All-in-One For Dummies Jack A. Hyman, Luca Massaron, Paul McFedries, John Paul Mueller, Lillian Pierson, Jonathan Reichental, Joseph Schmuller, Alan R. Simon, Allen G. Taylor, 2024-03-05 Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place. Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling. Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one. You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau. You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level. With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sources Organize and analyze data Use data to tell a story with Tableau Expand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data. Get ready to watch as your career in data takes off. |
| business analytics and data visualization: How Charts Lie: Getting Smarter about Visual Information Alberto Cairo, 2019-10-15 A leading data visualization expert explores the negative—and positive—influences that charts have on our perception of truth. Today, public conversations are increasingly driven by numbers. While charts, infographics, and diagrams can make us smarter, they can also deceive—intentionally or unintentionally. To be informed citizens, we must all be able to decode and use the visual information that politicians, journalists, and even our employers present us with each day. Demystifying an essential new literacy for our data-driven world, How Charts Lie examines contemporary examples ranging from election result infographics to global GDP maps and box office record charts, as well as an updated afterword on the graphics of the COVID-19 pandemic. |
| business analytics and data visualization: The Big Book of Dashboards Steve Wexler, Jeffrey Shaffer, Andy Cotgreave, 2017-04-24 The definitive reference book with real-world solutions you won't find anywhere else The Big Book of Dashboards presents a comprehensive reference for those tasked with building or overseeing the development of business dashboards. Comprising dozens of examples that address different industries and departments (healthcare, transportation, finance, human resources, marketing, customer service, sports, etc.) and different platforms (print, desktop, tablet, smartphone, and conference room display) The Big Book of Dashboards is the only book that matches great dashboards with real-world business scenarios. By organizing the book based on these scenarios and offering practical and effective visualization examples, The Big Book of Dashboards will be the trusted resource that you open when you need to build an effective business dashboard. In addition to the scenarios there's an entire section of the book that is devoted to addressing many practical and psychological factors you will encounter in your work. It's great to have theory and evidenced-based research at your disposal, but what will you do when somebody asks you to make your dashboard 'cooler' by adding packed bubbles and donut charts? The expert authors have a combined 30-plus years of hands-on experience helping people in hundreds of organizations build effective visualizations. They have fought many 'best practices' battles and having endured bring an uncommon empathy to help you, the reader of this book, survive and thrive in the data visualization world. A well-designed dashboard can point out risks, opportunities, and more; but common challenges and misconceptions can make your dashboard useless at best, and misleading at worst. The Big Book of Dashboards gives you the tools, guidance, and models you need to produce great dashboards that inform, enlighten, and engage. |
| business analytics and data visualization: Data Visualization Made Simple Kristen Sosulski, 2018-09-27 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. |
| business analytics and data visualization: Business Analytics, Volume II Amar Sahay, 2019-11-08 This business analytics (BA) text discusses the models based on fact-based data to measure past business performance to guide an organization in visualizing and predicting future business performance and outcomes. It provides a comprehensive overview of analytics in general with an emphasis on predictive analytics. Given the booming interest in analytics and data science, this book is timely and informative. It brings many terms, tools, and methods of analytics together. The first three chapters provide an introduction to BA, importance of analytics, types of BA-descriptive, predictive, and prescriptive-along with the tools and models. Business intelligence (BI) and a case on descriptive analytics are discussed. Additionally, the book discusses on the most widely used predictive models, including regression analysis, forecasting, data mining, and an introduction to recent applications of predictive analytics-machine learning, neural networks, and artificial intelligence. The concluding chapter discusses on the current state, job outlook, and certifications in analytics. |
| business analytics and data visualization: Data Visualization for Oracle Business Intelligence 11g Dan Vlamis, Tim Vlamis, 2015-02-13 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 11g. 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 11g 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 |
| business analytics and data visualization: Applications of Big Data in Large- and Small-Scale Systems Goundar, Sam, Rayani, Praveen Kumar, 2021-01-15 With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems. |
| business analytics and data visualization: Global Business Intelligence J Mark Munoz, 2017-11-10 Global Business Intelligence refers to an organization’s ability to gather, process and analyze pertinent international information in order to make optimal business decisions in a timely manner. With a challenging economic and geopolitical environment, companies and executives need to be adept at information gathering in order to manage emerging challenges and gain competitive advantages. This book Global Business Intelligence assembles a cast of international experts and thought leaders and explores the implications of business intelligence on contemporary management. Global Business Intelligence will be a key resource for researchers, academics, students and policy makers alike in the fields of International Business & Management, Business Strategy, and Geopolitics as well as related disciplines like Political Science, Economics, and Geography. |
| business analytics and data visualization: SPSS Statistics for Data Analysis and Visualization Keith McCormick, Jesus Salcedo, 2017-05-01 Dive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These hidden tools can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need. |
| business analytics and data visualization: Interactive Visual Data Analysis Christian Tominski, Heidrun Schumann, 2020-04-01 In the age of big data, being able to make sense of data is an important key to success. 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. Addressing today’s large and complex data, the book covers relevant automatic analytical computations to support the visual data analysis. 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. Features: Dedicated to the synthesis of visual, interactive, and analysis methods Systematic top-down view on visualization, interaction, and automatic analysis Broad coverage of fundamental and advanced visualization techniques Comprehensive chapter on interacting with visual representations Extensive integration of automatic computational methods Accessible portrayal of cutting-edge visual analytics technology Foreword by Jack van Wijk For more information, you can also visit the author website, where the book's figures are made available under the CC BY Open Access license. |
| business analytics and data visualization: Data Visualization for Business Decisions Andres Fortino, 2020-07 This workbook is intended for businessanalysts who wish to improve their skills in creating data visuals, presentations, and report illustrations used to support business decisions. It is a qualitative lab to develop the power of visualization and discrimination. It does not require the reader to modify charts, but to analyze and describe what would improve charts. In a set of controlled exercises, the reader istaken through the eighteen elements of six dimensions of analyzing and improving charts, visuals and reports used to communicate business concepts. Includescompanion files with videos, sample files, and slides used in examples from thebook. Features: Includes eighteen labs, three for each of the six major dimensions of data visuals: Story, Signs, Purpose, Perception, Method,and Charts Uses a comprehensive RAIKS (Rapid Assessment of Individual Knowledge and Skills) survey to judge readers' progress before and after using the text Provides a capstone exercise to review the aggregate analysis and final results for the two analyzed charts Companion files that include video tutorials and all of the sample files and templates used in the book's examples |
| business analytics and data visualization: Visualization Analysis and Design Tamara Munzner, 2014-12-01 Learn How to Design Effective Visualization SystemsVisualization Analysis and Design provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices. The book features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques |
| business analytics and data visualization: Data Visualization Kieran Healy, 2018-12-18 An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions |
| business analytics and data visualization: Predictive Analytics For Dummies Anasse Bari, Mohamed Chaouchi, Tommy Jung, 2014-03-06 Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big Data Predictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions. Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more. Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businesses Helps readers see how to shepherd predictive analytics projects through their companies Explains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and more Covers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing data Also covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewhere Propose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies. |
| business analytics and data visualization: A Business Analyst's Introduction to Business Analytics Adam Fleischhacker, 2020-07-20 This up-to-date business analytics textbook (published in July 2020) will get you harnessing the power of the R programming language to: manipulate and model data, discover and communicate insight, to visually communicate that insight, and successfully advocate for change within an organization. Book Description A frequent teaching-award winning professor with an analytics-industry background shares his hands-on guide to learning business analytics. It is the first textbook addressing a complete and modern business analytics workflow that includes data manipulation, data visualization, modelling business problems with graphical models, translating graphical models into code, and presenting insights back to stakeholders. Book Highlights Content that is accessible to anyone, even most analytics beginners. If you have taken a stats course, you are good to go. Assumes no knowledge of the R programming language. Provides introduction to R, RStudio, and the Tidyverse. Provides a solid foundation and an implementable workflow for anyone wading into the Bayesian inference waters. Provides a complete workflow within the R-ecosystem; there is no need to learn several programming languages or work through clunky interfaces between software tools. First book introducing two powerful R-packages - `causact` for visual modelling of business problems and `greta` which is an R interface to `TensorFlow` used for Bayesian inference. Uses the intuitive coding practices of the `tidyverse` including using `dplyr` for data manipulation and `ggplot2` for data visualization. Datasets that are freely and easily accessible. Code for generating all results and almost every visualization used in the textbook. Do not learn statistical computation or fancy math in a vacuum, learn it through this guide within the context of solving business problems. |
| business analytics and data visualization: Innovative Approaches of Data Visualization and Visual Analytics Mao Lin Huang, 2014 Due to rapid advances in hardware and software technologies, network infrastructure and data have become increasingly complex, requiring efforts to more effectively comprehend and analyze network topologies and information systems. Innovative Approaches of Data Visualization and Visual Analytics evaluates the latest trends and developments in force-based data visualization techniques, addressing issues in the design, development, evaluation, and application of algorithms and network topologies. This book will assist professionals and researchers working in the fields of data analysis and information science, as well as students in computer science and computer engineering, in developing increasingly effective methods of knowledge creation, management, and preservation. |
| business analytics and data visualization: Good Charts Scott Berinato, 2016-04-26 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. For a long time “dataviz” was left to specialists—data scientists and professional designers. 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. What’s more, building good charts is quickly becoming a need-to-have skill for managers. If you’re not doing it, other managers are, and they’re getting noticed for it and getting credit for contributing to your company’s success. 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 1980s—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. It taps into both well-established and cutting-edge research in visual perception and neuroscience, as well as the emerging field of visualization science, to explore why good charts (and bad ones) create “feelings behind our eyes.” Along the way, Berinato also includes many engaging vignettes of dataviz pros, illustrating the ideas in practice. Good Charts will help you turn plain, uninspiring charts that merely present information into smart, effective visualizations that powerfully convey ideas. |
| business analytics and data visualization: High Impact Data Visualization with Power View, Power Map, and Power BI Adam Aspin, 2014-06-24 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. |
| business analytics and data visualization: Mastering Data Visualization with Tableau Dr. Arpana Chaturvedi, Prof. Praveen Malik, 2024-07-11 DESCRIPTION Mastering Data Visualization with Tableau” is an invaluable book that will help you become more knowledgeable and elevate your understanding and skills in data visualization using Tableau which is one of the leading tools in the industry. This comprehensive resource covers the basics of visual analytics, explaining both the theory and practical ways to turn raw data into useful insights. You will start with Tableau Desktop by learning to download it, navigate the interface, and connect to data sources. The book teaches you to create and format basic charts, adding interactivity with parameters, sets, sorting, and filtering. You will explore calculations and advanced visualizations like bar-in-bar charts and maps. It covers designing interactive dashboards, using text and images for storytelling, and sharing work via PDFs and Tableau Public. The book ends with AI features in Tableau and hands-on exercises to practice. Through this book, readers can gain the confidence to handle complex datasets, apply advanced visualization techniques, and harness Tableau's full potential to make informed decisions faster and with greater accuracy. This guide is your pathway to becoming proficient in the art and science of data visualization with Tableau. KEY FEATURES ● Detailed exploration of Tableau, Tableau interface, dimensions, measures, and other visualization tools. ● Techniques for interactive data visualization using actions, filters, sets, parameters, groups, and hierarchy. ● Advanced graphing techniques and dynamic visualization strategies, calculated fields, table calculations, and LOD. ● Comprehensive integration of AI to improve data analysis. WHAT YOU WILL LEARN ● Tableau for complex data visualizations and apply predictive analytics. Clean and prepare data efficiently and create interactive dashboards that drive strategic business decisions. ● Advanced charts like bar-in-bar, profit calendar, and map visualizations. ● Gain practical hands-on experience with a question bank based on various industry use cases, enhancing your ability to tackle real-world data challenges. WHO THIS BOOK IS FOR This book is an excellent resource for students from any discipline, data scientists, business analysts, and professionals eager to master Tableau for comprehensive insights, effective dashboards, and advanced data analysis. TABLE OF CONTENTS 1. Introduction to Data Visualization and Visual Analytics 2. Getting Started with Tableau Desktop 3. Connecting to Data Sources and Data Interpretation 4. Basic Data Visualization and Graphs in Tableau 5. Dynamic Interaction: Parameters, Set, Hierarchies, and Sorting 6. Dynamic Interaction Using Filter and Action on Worksheet 7. Advanced Data Visualization and Graphs in Tableau 8. Calculations in Tableau 9. Dashboard Design and Story Creation 10. Enhancing Dashboards: Sharing and Collaboration 11. Integrating AI in Tableau: An Overview 12. Data Cleaning and Preparation Using Tableau Prep Builder |
| business analytics and data visualization: Sport Business Analytics C. Keith Harrison, Scott Bukstein, 2016-11-18 Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group. The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in: Ticket pricing Season ticket member retention Fan engagement Sponsorship valuation Customer relationship management Digital marketing Market research Data visualization. This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations. Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics. |
| business analytics and data visualization: Data Analysis and Visualization Using Python Dr. Ossama Embarak, 2018-11-20 Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python. Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python. In conclusion, you will complete a detailed case study, where you’ll get a chance to revisit the concepts you’ve covered so far. What You Will LearnUse Python programming techniques for data science Master data collections in Python Create engaging visualizations for BI systems Deploy effective strategies for gathering and cleaning data Integrate the Seaborn and Matplotlib plotting systems Who This Book Is For Developers with basic Python programming knowledge looking to adopt key strategies for data analysis and visualizations using Python. |
| business analytics and data visualization: Making Data Visual Danyel Fisher, Miriah Meyer, 2017-12-20 You have a mound of data sitting in front of you and a suite of computation tools at your disposal. And yet, you're stumped as to how to turn that data into insight. Which part of that data actually matters, and where is this insight hidden? If you're a data scientist who struggles to navigate the murky space between data and insight, this book will help you think about and reshape data for visual data exploration. It's ideal for relatively new data scientists, who may be computer-knowledgeable and data-knowledgeable, but do not yet know how to create effective, explorable representations of data. With this book, you'll learn: Task analysis, driven by a series of leading questions that draw out the important aspects of the data to be explored; Visualization patterns, each of which take a different perspective on data and answer different questions; A taxonomy of visualizations for common data types; Techniques for gathering design requirements; When and where to make use of statistical methods.-- |
| business analytics and data visualization: Data Visualization with Excel Dashboards and Reports Dick Kusleika, 2021-02-05 Large corporations like IBM and Oracle are using Excel dashboards and reports as a Business Intelligence tool, and many other smaller businesses are looking to these tools in order to cut costs for budgetary reasons. An effective analyst not only has to have the technical skills to use Excel in a productive manner but must be able to synthesize data into a story, and then present that story in the most impactful way. Microsoft shows its recognition of this with Excel. In Excel, there is a major focus on business intelligence and visualization. Data Visualization with Excel Dashboards and Reports fills the gap between handling data and synthesizing data into meaningful reports. This title will show readers how to think about their data in ways other than columns and rows. Most Excel books do a nice job discussing the individual functions and tools that can be used to create an Excel Report. Titles on Excel charts, Excel pivot tables, and other books that focus on Tips and Tricks are useful in their own right; however they don't hit the mark for most data analysts. The primary reason these titles miss the mark is they are too focused on the mechanical aspects of building a chart, creating a pivot table, or other functionality. They don't offer these topics in the broader picture by showing how to present and report data in the most effective way. What are the most meaningful ways to show trending? How do you show relationships in data? When is showing variances more valuable than showing actual data values? How do you deal with outliers? How do you bucket data in the most meaningful way? How do you show impossible amounts of data without inundating your audience? In Data Visualization with Excel Reports and Dashboards, readers will get answers to all of these questions. Part technical manual, part analytical guidebook; this title will help Excel users go from reporting data with simple tables full of dull numbers, to creating hi-impact reports and dashboards that will wow management both visually and substantively. This book offers a comprehensive review of a wide array of technical and analytical concepts that will help users create meaningful reports and dashboards. After reading this book, the reader will be able to: Analyze large amounts of data and report their data in a meaningful way Get better visibility into data from different perspectives Quickly slice data into various views on the fly Automate redundant reporting and analyses Create impressive dashboards and What-If analyses Understand the fundamentals of effective visualization Visualize performance comparisons Visualize changes and trends over time |
| business analytics and data visualization: Data Mining for Business Analytics Galit Shmueli, Peter C. Bruce, Nitin R. Patel, 2016-04-18 An applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: Real-world examples to build a theoretical and practical understanding of key data mining methods End-of-chapter exercises that help readers better understand the presented material Data-rich case studies to illustrate various applications of data mining techniques Completely new chapters on social network analysis and text mining A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides https://www.dataminingbook.com Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. Praise for the Second Edition ...full of vivid and thought-provoking anecdotes... needs to be read by anyone with a serious interest in research and marketing.– Research Magazine Shmueli et al. have done a wonderful job in presenting the field of data mining - a welcome addition to the literature. – ComputingReviews.com Excellent choice for business analysts...The book is a perfect fit for its intended audience. – Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks and book chapters. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad for 15 years. |
| business analytics and data visualization: Data at Work Jorge Camões, 2016-04-08 Information visualization is a language. Like any language, it can be used for multiple purposes. A poem, a novel, and an essay all share the same language, but each one has its own set of rules. The same is true with information visualization: a product manager, statistician, and graphic designer each approach visualization from different perspectives. Data at Work was written with you, the spreadsheet user, in mind. This book will teach you how to think about and organize data in ways that directly relate to your work, using the skills you already have. In other words, you don’t need to be a graphic designer to create functional, elegant charts: this book will show you how. Although all of the examples in this book were created in Microsoft Excel, this is not a book about how to use Excel. Data at Work will help you to know which type of chart to use and how to format it, regardless of which spreadsheet application you use and whether or not you have any design experience. In this book, you’ll learn how to extract, clean, and transform data; sort data points to identify patterns and detect outliers; and understand how and when to use a variety of data visualizations including bar charts, slope charts, strip charts, scatter plots, bubble charts, boxplots, and more. Because this book is not a manual, it never specifies the steps required to make a chart, but the relevant charts will be available online for you to download, with brief explanations of how they were created. |
| business analytics and data visualization: Insightful Data Visualization with SAS Viya Falko Schulz, Travis Murphy, 2020-10-26 Elevate your storytelling with SAS Visual Analytics Data visualization is the gateway to artificial intelligence (AI) and big data. Insightful Data Visualization with SAS Viya shows how the latest SAS Viya tools can be used to create data visualizations in an easier, smarter, and more engaging way than ever before. SAS Visual Analytics combined with human creativity can produce endless possibilities. In this book, you will learn tips and techniques for getting the most from your SAS Visual Analytics investment. From beginners to advanced SAS users, this book has something for everyone. Use AI wizards to create data visualization automatically, learn to use advanced analytics in your dashboards to surface smarter insights, and learn to extend SAS Visual Analytics with advanced integrations and options. Topics covered in this book include: SAS Visual Analytics Data visualization with SAS Reports and dashboards SAS code examples Self-service analytics SAS data access Extending SAS beyond drag and drop |
| business analytics and data visualization: Python: Data Analytics and Visualization Phuong Vo.T.H, Martin Czygan, Ashish Kumar, Kirthi Raman, 2017-03-31 Understand, evaluate, and visualize data About This Book Learn basic steps of data analysis and how to use Python and its packages A step-by-step guide to predictive modeling including tips, tricks, and best practices Effectively visualize a broad set of analyzed data and generate effective results Who This Book Is For This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner. What You Will Learn Get acquainted with NumPy and use arrays and array-oriented computing in data analysis Process and analyze data using the time-series capabilities of Pandas Understand the statistical and mathematical concepts behind predictive analytics algorithms Data visualization with Matplotlib Interactive plotting with NumPy, Scipy, and MKL functions Build financial models using Monte-Carlo simulations Create directed graphs and multi-graphs Advanced visualization with D3 In Detail You will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn. After this, you will move on to a data analytics specialization—predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predictive models from data. You will get balanced information on statistical and mathematical concepts, and implement them in Python using libraries such as Pandas, scikit-learn, and NumPy. You'll learn more about the best predictive modeling algorithms such as Linear Regression, Decision Tree, and Logistic Regression. Finally, you will master best practices in predictive modeling. After this, you will get all the practical guidance you need to help you on the journey to effective data visualization. Starting with a chapter on data frameworks, which explains the transformation of data into information and eventually knowledge, this path subsequently cover the complete visualization process using the most popular Python libraries with working examples This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Getting Started with Python Data Analysis, Phuong Vo.T.H &Martin Czygan Learning Predictive Analytics with Python, Ashish Kumar Mastering Python Data Visualization, Kirthi Raman Style and approach The course acts as a step-by-step guide to get you familiar with data analysis and the libraries supported by Python with the help of real-world examples and datasets. It also helps you gain practical insights into predictive modeling by implementing predictive-analytics algorithms on public datasets with Python. The course offers a wealth of practical guidance to help you on this journey to data visualization |
| business analytics and data visualization: Business Analytics Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, 2020-03-10 Present the full range of analytics -- from descriptive and predictive to prescriptive analytics -- with Camm/Cochran/Fry/Ohlmann's market-leading BUSINESS ANALYTICS, 4E. Clear, step-by-step instructions teach students how to use Excel, Tableau, R and JMP Pro to solve more advanced analytics concepts. As instructor, you have the flexibility to choose your preferred software for teaching concepts. Extensive solutions to problems and cases save grading time, while providing students with critical practice. This edition covers topics beyond the traditional quantitative concepts, such as data visualization and data mining, which are increasingly important in today's analytical problem solving. In addition, MindTap and WebAssign customizable digital course solutions offer an interactive eBook, auto-graded exercises from the printed book, algorithmic practice problems with solutions and Exploring Analytics visualizations to strengthen students' understanding of course concepts. |
| business analytics and data visualization: Storytelling with Data Cole Nussbaumer Knaflic, 2015-10-07 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! |
| business analytics and data visualization: Data Analytics and Visualization in Quality Analysis using Tableau Jaejin Hwang, Youngjin Yoon, 2021-07-28 Data Analytics and Visualization in Quality Analysis using Tableau goes beyond the existing quality statistical analysis. It helps quality practitioners perform effective quality control and analysis using Tableau, a user-friendly data analytics and visualization software. It begins with a basic introduction to quality analysis with Tableau including differentiating factors from other platforms. It is followed by a description of features and functions of quality analysis tools followed by step-by-step instructions on how to use Tableau. Further, quality analysis through Tableau based on open source data is explained based on five case studies. Lastly, it systematically describes the implementation of quality analysis through Tableau in an actual workplace via a dashboard example. Features: Describes a step-by-step method of Tableau to effectively apply data visualization techniques in quality analysis Focuses on a visualization approach for practical quality analysis Provides comprehensive coverage of quality analysis topics using state-of-the-art concepts and applications Illustrates pragmatic implementation methodology and instructions applicable to real-world and business cases Include examples of ready-to-use templates of customizable Tableau dashboards This book is aimed at professionals, graduate students and senior undergraduate students in industrial systems and quality engineering, process engineering, systems engineering, quality control, quality assurance and quality analysis. |
| business analytics and data visualization: Visualizing with Text Richard Brath, 2020-11-01 Visualizing with Text uncovers the rich palette of text elements usable in visualizations from simple labels through to documents. Using a multidisciplinary research effort spanning across fields including visualization, typography, and cartography, it builds a solid foundation for the design space of text in visualization. The book illustrates many new kinds of visualizations, including microtext lines, skim formatting, and typographic sets that solve some of the shortcomings of well-known visualization techniques. Key features: More than 240 illustrations to aid inspiration of new visualizations Eight new approaches to data visualization leveraging text Quick reference guide for visualization with text Builds a solid foundation extending current visualization theory Bridges between visualization, typography, text analytics, and natural language processing The author website, including teaching exercises and interactive demos and code, can be found here. Designers, developers, and academics can use this book as a reference and inspiration for new approaches to visualization in any application that uses text. |
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