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Produktbild: The Visual Organization

The Visual Organization Data Visualization, Big Data, and the Quest for Better Decisions

Aus der Reihe SAS Institute Inc

59,99 €

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

24.03.2014

Verlag

John Wiley & Sons

Seitenzahl

240

Maße (L/B/H)

26,3/18,9/2,3 cm

Gewicht

753 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-118-79438-8

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

24.03.2014

Verlag

John Wiley & Sons

Seitenzahl

240

Maße (L/B/H)

26,3/18,9/2,3 cm

Gewicht

753 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-118-79438-8

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: GPSR Kontakt

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  • Produktbild: The Visual Organization
  • List of Figures and Tables xvii

    Preface xix

    Acknowledgments xxv

    How to Help This Book xxvii

    Part I Book Overview and Background 1

    Introduction 3

    Adventures in Twitter Data Discovery 4

    Contemporary Dataviz 101 9

    Primary Objective 9

    Benefits 11

    More Important Than Ever 13

    Revenge of the Laggards: The Current State of Dataviz 15

    Book Overview 18

    Defining the Visual Organization 19

    Central Thesis of Book 19

    Cui Bono? 20

    Methodology: Story Matters Here 21

    The Quest for Knowledge and Case Studies 24

    Differentiation: A Note on Other Dataviz Texts 25

    Plan of Attack 26

    Next 27

    Notes 27

    Chapter 1 The Ascent of the Visual Organization 29

    The Rise of Big Data 30

    Open Data 30

    The Burgeoning Data Ecosystem 33

    The New Web: Visual, Semantic, and API-Driven 34

    The Arrival of the Visual Web 34

    Linked Data and a More Semantic Web 35

    The Relative Ease of Accessing Data 36

    Greater Efficiency via Clouds and Data Centers 37

    Better Data Tools 38

    Greater Organizational Transparency 40

    The Copycat Economy: Monkey See, Monkey Do 41

    Data Journalism and the Nate Silver Effect 41

    Digital Man 44

    The Arrival of the Visual Citizen 44

    Mobility 47

    The Visual Employee: A More Tech- and Data-Savvy Workforce 47

    Navigating Our Data-Driven World 48

    Next 49

    Notes 49

    Chapter 2 Transforming Data into Insights: The Tools 51

    Dataviz: Part of an Intelligent and Holistic Strategy 52

    The Tyranny of Terminology: Dataviz, BI, Reporting, Analytics, and KPIs 53

    Do Visual Organizations Eschew All Tried-and-True Reporting Tools? 55

    Drawing Some Distinctions 56

    The Dataviz Fab Five 57

    Applications from Large Enterprise Software Vendors 57

    LESVs: The Case For 58

    LESVs: The Case Against 59

    Best-of-Breed Applications 61

    Cost 62

    Ease of Use and Employee Training 62

    Integration and the Big Data World 63

    Popular Open-Source Tools 64

    D3.js 64

    R 65

    Others 66

    Design Firms 66

    Startups, Web Services, and Additional Resources 70

    The Final Word: One Size Doesn't Fit All 72

    Next 73

    Notes 73

    Part II Introducing the Visual Organization 75

    Chapter 3 The Quintessential Visual Organization 77

    Netflix 1.0: Upsetting the Applecart 77

    Netflix 2.0: Self-Cannibalization 78

    Dataviz: Part of a Holistic Big Data Strategy 80

    Dataviz: Imbued in the Netflix Culture 81

    Customer Insights 82

    Better Technical and Network Diagnostics 84

    Embracing the Community 88

    Lessons 89

    Next 90

    Notes 90

    Chapter 4 Dataviz in the DNA 93

    The Beginnings 94

    UX Is Paramount 95

    The Plumbing 97

    Embracing Free and Open-Source Tools 98

    Extensive Use of APIs 101

    Lessons 101

    Next 102

    Note 102

    Chapter 5 Transparency in Texas 103

    Background 104

    Early Dataviz Efforts 105

    Embracing Traditional BI 106

    Data Discovery 107

    Better Visibility into Student Life 108

    Expansion: Spreading Dataviz Throughout the System 110

    Results 111

    Lessons 113

    Next 113

    Notes 114

    Part III Getting Started: Becoming a Visual Organization 115

    Chapter 6 The Four-Level Visual Organization Framework 117

    Big Disclaimers 118

    A Simple Model 119

    Limits and Clarifications 120

    Progression 122

    Is Progression Always Linear? 123

    Can a Small Organization Best Position Itself to Reach Levels 3 and 4? If So, How? 123

    Can an Organization Start at Level 3 or 4 and Build from the Top Down? 123

    Is Intralevel Progression Possible? 123

    Are Intralevel and Interlevel Progression Inevitable? 123

    Can Different Parts of the Organization Exist on Different Levels? 124

    Should an Organization Struggling with Levels 1 and 2 Attempt to Move to Level 3 or 4? 124

    Regression: Reversion to Lower Levels 124

    Complements, Not Substitutes 125

    Accumulated Advantage 125

    The Limits of Lower Levels 125

    Relativity and Sublevels 125

    Should Every Organization Aspire to Level 4? 126

    Next 126

    Chapter 7 WWVOD? 127

    Visualizing the Impact of a Reorg 128

    Visualizing Employee Movement 129

    Starting Down the Dataviz Path 129

    Results and Lessons 133

    Future 135

    A Marketing Example 136

    Next 137

    Notes 137

    Chapter 8 Building the Visual Organization 139

    Data Tips and Best Practices 139

    Data: The Primordial Soup 139

    Walk Before You Run . . . At Least for Now 140

    A Dataviz Is Often Just the Starting Point 140

    Visualize Both Small and Big Data 141

    Don't Forget the Metadata 141

    Look Outside of the Enterprise 143

    The Beginnings: All Data Is Not Required 143

    Visualize Good and Bad Data 144

    Enable Drill-Down 144

    Design Tips and Best Practices 148

    Begin with the End in Mind (Sort of) 148

    Subtract When Possible 150

    UX: Participation and Experimentation Are Paramount 150

    Encourage Interactivity 151

    Use Motion and Animation Carefully 151

    Use Relative--Not Absolute--Figures 151

    Technology Tips and Best Practices 152

    Where Possible, Consider Using APIs 152

    Embrace New Tools 152

    Know the Limitations of Dataviz Tools 153

    Be Open 153

    Management Tips and Best Practices 154

    Encourage Self-Service, Exploration, and Data Democracy 154

    Exhibit a Healthy Skepticism 154

    Trust the Process, Not the Result 155

    Avoid the Perils of Silos and Specialization 156

    If Possible, Visualize 156

    Seek Hybrids When Hiring 157

    Think Direction First, Precision Later 157

    Next 158

    Notes 158

    Chapter 9 The Inhibitors: Mistakes, Myths, and Challenges 159

    Mistakes 160

    Falling into the Traditional ROI Trap 160

    Always--and Blindly--Trusting a Dataviz 161

    Ignoring the Audience 162

    Developing in a Cathedral 162

    Set It and Forget It 162

    Bad Dataviz 163

    TMI 163

    Using Tiny Graphics 163

    Myths 165

    Data-visualizations Guarantee Certainty and Success 165

    Data Visualization Is Easy 165

    Data Visualizations Are Projects 166

    There Is One "Right" Visualization 166

    Excel Is Sufficient 167

    Challenges 167

    The Quarterly Visualization Mentality 167

    Data Defiance 168

    Unlearning History: Overcoming the Disappointments of Prior Tools 168

    Next 169

    Notes 169

    Part IV Conclusion and the Future of Dataviz 171

    Coda: We're Just Getting Started 173

    Four Critical Data-Centric Trends 175

    Wearable Technology and the Quantified Self 175

    Machine Learning and the Internet of Things 176

    Multidimensional Data 177

    The Forthcoming Battle Over Data Portability and Ownership 179

    Final Thoughts: Nothing Stops This Train 181

    Notes 182

    Afterword: My Life in Data 183

    Appendix: Supplemental Dataviz Resources 187

    Selected Bibliography 191

    About the Author 193

    Index 195