LEADER 06325nam 2200745 450 001 9910787881703321 005 20200520144314.0 010 $a1-118-85834-4 010 $a1-118-85841-7 035 $a(CKB)2670000000530800 035 $a(EBL)1638155 035 $a(SSID)ssj0001133153 035 $a(PQKBManifestationID)11636070 035 $a(PQKBTitleCode)TC0001133153 035 $a(PQKBWorkID)11156240 035 $a(PQKB)11028966 035 $a(DLC) 2013049074 035 $a(Au-PeEL)EBL1638155 035 $a(CaPaEBR)ebr10842317 035 $a(CaONFJC)MIL578573 035 $a(OCoLC)865074285 035 $a(CaSebORM)9781118794388 035 $a(CaSebORM)3642621704001 035 $a(MiAaPQ)EBC1638155 035 $a(EXLCZ)992670000000530800 100 $a20140313h20142014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 14$aThe visual organization $edata visualization, big data, and the quest for better decisions /$fPhil Simon 205 $a1st edition 210 1$aHoboken, New Jersey :$cWiley,$d2014. 210 4$dİ2014 215 $a1 online resource (236 p.) 225 1 $aWiley & SAS Business Series 300 $aDescription based upon print version of record. 311 $a1-118-79438-9 320 $aIncludes bibliographical references and index. 327 $aThe 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 327 $aChapter 1 The Ascent of the Visual OrganizationThe 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 327 $aNavigating Our Data-Driven WorldNext; 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 327 $aDesign FirmsStart-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 327 $aExtensive Use of APIsLessons; 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? 327 $aCan an Organization Start at Level 3 or 4 and Build from the Top Down? 330 $a"The era of Big Data as arrived, and most organizations are woefully unprepared. Slowly, many are discovering that stalwarts like Excel spreadsheets, KPIs, standard reports, and even traditional business intelligence tools aren't sufficient. These old standbys can't begin to handle today's increasing streams, volumes, and types of data. Amidst all of the chaos, though, a new type of organization is emerging. In The Visual Organization, award-winning author and technology expert Phil Simon looks at how an increasingly number of organizations are embracing new dataviz tools and, more important, a new mind-set based upon data discovery and exploration. Simon adroitly shows how Amazon, Apple, Facebook, Google, Twitter, and other tech heavyweights use powerful data visualization tools to garner fascinating insights into their businesses. But make no mistake: these companies are hardly alone. Organizations of all types, industries, sizes are representing their data in new and amazing ways. As a result, they are asking better questions and making better business decisions. Rife with real-world examples and case studies, The Visual Organization is a full-color tour-de-force"--$cProvided by publisher. 410 0$aWiley and SAS business series. 606 $aInformation technology$xManagement 606 $aInformation visualization 606 $aBig data 606 $aBusiness$xData processing 615 0$aInformation technology$xManagement. 615 0$aInformation visualization. 615 0$aBig data. 615 0$aBusiness$xData processing. 676 $a658.4/038 700 $aSimon$b Phil$0901229 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910787881703321 996 $aThe visual organization$93848973 997 $aUNINA