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Author Simon, Phil
Title The Visual Organization : Data Visualization, Big Data, and the Quest for Better Decisions
Imprint New York : John Wiley & Sons, Incorporated, 2014
©2014
book jacket
Edition 1st ed
Descript 1 online resource (236 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Series Wiley and SAS Business Ser
Wiley and SAS Business Ser
Note Intro -- The Visual Organization -- Contents -- List of Figures and Tables -- Preface: A Tale of Two IPOs -- Acknowledgments -- How to Help This Book -- Part One Book Overview and Background -- Introduction -- Adventures in Twitter Data Discovery -- Contemporary Dataviz 101 -- Primary Objective -- Benefits -- More Important Than Ever -- Revenge of the Laggards: The Current State of Dataviz -- Book Overview -- Defining the Visual Organization -- Central Thesis of This Book -- Cui Bono? -- Methodology: Story Matters Here -- The Quest for Knowledge and Case Studies -- Differentiation: A Note on Other Dataviz Texts -- Plan of Attack -- Next -- Notes -- Chapter 1 The Ascent of the Visual Organization -- The Rise of Big Data -- Open Data -- The Burgeoning Data Ecosystem -- The New Web: Visual, Semantic, and API-Driven -- The Arrival of the Visual Web -- Linked Data and a More Semantic Web -- The Relative Ease of Accessing Data -- Greater Efficiency via Clouds and Data Centers -- Better Data Tools -- Greater Organizational Transparency -- The Copycat Economy: Monkey See, Monkey Do -- Data Journalism and the Nate Silver Effect -- Digital Man -- The Arrival of the Visual Citizen -- Mobility -- The Visual Employee: A More Tech- and Data-Savvy Workforce -- Navigating Our Data-Driven World -- Next -- Notes -- Chapter 2 Transforming Data into Insights: The Tools -- Dataviz: Part of an Intelligent and Holistic Strategy -- The Tyranny of Terminology: Dataviz, BI, Reporting, Analytics, and KPIs -- Do Visual Organizations Eschew All Tried-and-True Reporting Tools? -- Drawing Some Distinctions -- The Dataviz Fab Five -- Applications from Large Enterprise Software Vendors -- LESVs: The Case For -- LESVs: The Case Against -- Best-of-Breed Applications -- Cost -- Ease of Use and Employee Training -- Integration and the Big Data World -- Popular Open-Source Tools
D3.js -- R -- Others -- Design Firms -- Start-Ups, Web Services, and Additional Resources -- The Final Word: One Size Doesn't Fit All -- Next -- Notes -- Part Two Introducing the Visual Organization -- Chapter 3 The Quintessential Visual Organization -- Netflix 1.0: Upsetting the Applecart -- Netflix 2.0: Self-Cannibalization -- Dataviz: Part of a Holistic Big Data Strategy -- Dataviz: Imbued in the Netflix Culture -- Customer Insights -- Better Technical and Network Diagnostics -- Embracing the Community -- Lessons -- Next -- Notes -- Chapter 4 Dataviz in the DNA -- The Beginnings -- UX Is Paramount -- The Plumbing -- Embracing Free and Open-Source Tools -- Extensive Use of APIs -- Lessons -- Next -- Notes -- Chapter 5 Transparency in Texas -- Background -- Early Dataviz Efforts -- Embracing Traditional BI -- Data Discovery -- Better Visibility into Student Life -- Expansion: Spreading Dataviz Throughout the System -- Results -- Lessons -- Next -- Notes -- Part Three Getting Started: Becoming a Visual Organization -- Chapter 6 The Four-Level Visual Organization Framework -- Big Disclaimers -- A Simple Model -- Limits and Clarifications -- Progression -- Is Progression Always Linear? -- Can a Small Organization Best Position Itself to Reach Levels 3 and 4? If So, How? -- Can an Organization Start at Level 3 or 4 and Build from the Top Down? -- Is Intralevel Progression Possible? -- Are Intralevel and Interlevel Progression Inevitable? -- Can Different Parts of the Organization Exist on Different Levels? -- Should an Organization Struggling with Levels 1 and 2 Attempt to Move to Level 3 or 4? -- Regression: Reversion to Lower Levels -- Complements, Not Substitutes -- Accumulated Advantage -- The Limits of Lower Levels -- Relativity and Sublevels -- Should Every Organization Aspire to Level 4? -- Next -- Chapter 7 WWVOD?
Visualizing the Impact of a Reorg -- Visualizing Employee Movement -- Starting Down the Dataviz Path -- Results and Lessons -- Future -- A Marketing Example -- Next -- Notes -- Chapter 8 Building the Visual Organization -- Data Tips and Best Practices -- Data: The Primordial Soup -- Walk Before You Run . . . At Least for Now -- A Dataviz Is Often Just the Starting Point -- Visualize Both Small and Big Data -- Don't Forget the Metadata -- Look Outside of the Enterprise -- The Beginnings: All Data Is Not Required -- Visualize Good and Bad Data -- Enable Drill-Down -- Design Tips and Best Practices -- Begin with the End in Mind (Sort of) -- Subtract When Possible -- UX: Participation and Experimentation Are Paramount -- Encourage Interactivity -- Use Motion and Animation Carefully -- Use Relative-Not Absolute-Figures -- Technology Tips and Best Practices -- Where Possible, Consider Using APIs -- Embrace New Tools -- Know the Limitations of Dataviz Tools -- Be Open -- Management Tips and Best Practices -- Encourage Self-Service, Exploration, and Data Democracy -- Exhibit a Healthy Skepticism -- Trust the Process, Not the Result -- Avoid the Perils of Silos and Specialization -- If Possible, Visualize -- Seek Hybrids When Hiring -- Think Direction First, Precision Later -- Next -- Notes -- Chapter 9 The Inhibitors: Mistakes, Myths, and Challenges -- Mistakes -- Falling into the Traditional ROI Trap -- Always-and Blindly-Trusting a Dataviz -- Ignoring the Audience -- Developing in a Cathedral -- Set It and Forget It -- Bad Dataviz -- TMI -- Using Tiny Graphics -- Myths -- Data Visualizations Guarantee Certainty and Success -- Data Visualization Is Easy -- Data Visualizations Are Projects -- There Is One "Right" Visualization -- Excel Is Sufficient -- Challenges -- The Quarterly Visualization Mentality -- Data Defiance
Unlearning History: Overcoming the Disappointments of Prior Tools -- Next -- Notes -- Part Four Conclusion and the Future of Dataviz -- Coda: We're Just Getting Started -- Four Critical Data-Centric Trends -- Wearable Technology and the Quantified Self -- Machine Learning and the Internet of Things -- Multidimensional Data -- The Forthcoming Battle over Data Portability and Ownership -- Final Thoughts: Nothing Stops This Train -- Notes -- Afterword: My Life in Data -- Supplemental Dataviz Resources -- Selected Bibliography -- About the Author -- Index
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
Description based on publisher supplied metadata and other sources
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2020. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
Link Print version: Simon, Phil The Visual Organization : Data Visualization, Big Data, and the Quest for Better Decisions New York : John Wiley & Sons, Incorporated,c2014 9781118794388
Subject Big data
Electronic books
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