The visual imperative: creating a visual culture of data discovery
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam ; Boston ; Heidelberg ; London ; New York ; Oxford ; Paris ; San Diego ; San Francisco ; Singapore ; Sydney ; Tokyo
Elsevier Morgan Kaufmann
[2016]
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXVI, 293 Seiten Illustrationen |
| ISBN: | 9780128038444 |
Internformat
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| 245 | 1 | 0 | |a The visual imperative |b creating a visual culture of data discovery |c Lindy Ryan |
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| 264 | 4 | |c © 2016 | |
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Datensatz im Suchindex
| _version_ | 1804176142409662464 |
|---|---|
| adam_text | Contents
Foreword................................................................xv
Introduction...........................................................xix
About the Author................................................... xxiii
Acknowledgments........................................................xxv
PART I HOW DATA IS DRIVING BUSINESS DISRUPTION,
TRANSFORMATION, AND REINVENTION_______________________________
CHAPTER 1 Separating Leaders from Laggards_____________________________3
1.1 An Era of Disruption, Transformation, and Reinvention....4
1.1.1 Understand Disruption.............................6
1.1.2 Build Capabilities by Design......................7
1.1.3 Enable a Platform of Speed.......................10
1.2 Characteristics of Data-Centric Companies...............10
1.2.1 They are Data Harvesters..........................11
1.2.2 They Live an Analytic Culture.....................12
1.2.3 They Think Long Term..............................13
1.2.4 They Take Action.................................14
1.2.5 And, They Stay Connected..........................14
1.3 Examples of Data-Driven Companies........................15
1.3.1 Netflix..........................................15
1.3.2 Facebook.........................................16
1.3.3 Starbucks........................................19
1.3.4 Amazon...........................................20
1.4 From the Data to the Dashboard.........................21
1.5 Navigating This Book...................................23
References........................................-..........24
CHAPTER 2 Improved Agility and Insights Through
(Visual) Discovery.....................................27
2.1 The Discovery Imperative................................27
2.2 Business Intelligence Versus Data Discovery............28
2.3 The Business Impact of the Discovery Culture...........31
2.3.1 Fostering a Discovery Culture.....................33
2.3.2 Discovery Culture Challenges.....................34
2.3.3 Discovery Organizations as Ambidextrous by Design.35
2.4 The Role of Friction in Discovery......................35
Contents
2.5 The Four Forms of Discovery.................................J
2.5.1 Traditional Forms of Discovery........................32
2.5.2 Advanced Forms of Discovery...........................38
2.6 SQL: The Language of Discovery..............................39
2.6.1 SQL Capability and Compatibility......................41
2.6.2 Scalability...........................................42
2.6.3 Speed.................................................42
2.6.4 Thinking Long-Term....................................42
2.7 Discovery in the Days to Come...............................43
Reference........................................................43
CHAPTER 3 From Self-Service to Self-Sufficiency.............................45
3.1 From Self-Service to Self-Sufficiency.......................46
3.1.1 A Lesson from Frozen Yogurt...........................49
3.2 Discovery Capabilities for Self-Sufficiency.................51
3.2.1 Discovery Tools.......................................52
3.2.2 Discovery Environment.................................52
3.2.3 Discovery Access......................................53
3.3 (Information) Enablement Technology.........................54
3.4 The Data Scientist: The Sexiest of Them All.................55
3.4.1 The Blended Aptitudes of Data Scientist, PhD..........56
3.5 Moving Forward..............................................59
References.......................................................60
CHAPTER 4 Navigating Ethics in the Big Data Democracy.......................61
4.1 Introduction................................................61
4.2 Aftershocks of the Big Data Revolution......................62
4.3 Big Data’s Personal Impact..................................64
4.3.1 Social Graphs.........................................65
4.3.2 Data Ownership and Data Memory........................70
4.3.3 Passive Data Collection...............................71
4.3.4 Privacy in a Public World.............................72
4.4 Exercise: Ethical Data Scenarios............................72
4.4.1 Scenario One..........................................73
4.4.2 Scenario Two..........................................73
4.4.3 Scenario Three........................................74
4.5 Data Ethics in the News.....................................74
4.5.1 Facebook............................................. 74
4.5.2 Target..................................................
4.5.3 Ashley Madison....................................... 77
4.6 The Data Visualization Hippocratic Oath.................... 78
Contents ix
4.7 Ethics Requires Leadership.............................79
4.7.1 Emotional Intelligence............................80
4.7.2 Cultural Competence and Diversity in Data.........80
4.7.3 Adaptive Leadership as an Applied Approach........81
4.7.4 Finally, Critical Thinking Competence.............81
4.8 Closing Thoughts.......................................82
References................................................ 83
CHAPTER 5 The Data Science Education and Leadership
Landscape...............................................85
5.1 Introduction...........................................85
5.2 The New Data Science Student...........................85
5.2.1 Managing Complex Systems..........................87
5.2.2 Continuous Learning...............................87
5.2.3 Blending Research and Practice....................88
5.2.4 The Reality.......................................88
5.2.5 New University Programs and Vendor Participation.89
5.3 The New Digital Native.................................91
5.3.1 Leadership Qualities of the Millennial Leader.....94
5.3.2 Humility..........................................95
5.3.3 Hunger............................................96
5.3.4 Happiness.........................................96
5.4 Addressing the Gender Gap—Women in IT..................96
5.5 New Roles for New Leaders..............................99
5.5.1 The Data Visualization Analyst...................100
5.5.2 The Visualization Curator/Designer...............102
5.5.3 The Data Storyboard Artist.......................103
5.5.4 The Chief Storytelling Officer...................103
5.6 The Steps Beyond......................................104
References............................................... 105
PART II COMMUNICATING DATA VISUALLY____________________________________
CHAPTER 6 Visual Communication and Literacy.....................109
6.1 The History of Visual Communication...................110
6.1.1 Noteworthy Figures in Visual Communication.......116
6.2 Visual Memorability and Retention.....................116
6.2.1 Imagery Analysis.................................119
6.3 Extending Visual Literacy to Visual Data Literacy.....121
6.3.1 Visual Learning Key to Data Literacy.............122
6.3.2 Incorporating Data into Visual Learning..........124
X
Contents
6.3.3 Decode..............................................
6.3.4 Encode..............................................
6.3.5 Special Considerations for Visual Data
r I 9
Literacy Educators........................................1 zo
6.4 From Communication to Conversation.........................127
References.....................................................129
CHAPTER 7 Visual Storytelling with Data...................................131
7.1 The Storytelling Paradigm: Defining the Data Story........132
7.2 A Brief Bit of Story Psychology...........................133
7.2.1 An Anthropological Perspective.......................134
7.2.2 A Cognitive Perspective..............................135
7.3 The Data Narrative Framework...............................136
7.3.1 Inverted Journalism Pyramid.........................138
7.4 Five Steps to Data Storytelling with Visualization.........139
7.4.1 First, Find Data That Supports Your Story...........139
7.4.2 Then, Layer Information for Understanding............140
7.4.3 The Goal is to Design to Reveal.....................141
7.4.4 ...But Beware the False Reveal......................141
7.4.5 Tell it Fast - and Make it Mobile...................144
7.5 Storytelling Reconsidered, the Probability Problem.........145
7.5.1 The Storytelling Paradox.............................145
7.6 Storytelling’s Secret Ingredient: The Audience.............149
References.....................................................150
CHAPTER 8 The Importance of Visual Design.................................153
8.1 Data Visualization is a Beautiful Science..................154
8.2 Key Cognitive Elements in Visualization....................155
8.2.1 Patterns and Organization............................156
8.2.2 Color Use............................................158
8.2.3 Counting and Numerosity..............................159
8.3 Color 101..................................................160
8.3.1 Color Contingencies..................................161
8.4 Visual Design Building Blocks..............................165
8.4.1 Lines................................................165
8.4.2 Shapes...............................................167
8.4.3 Typography...........................................168
8.5 Visualization Constraints..................................171
8.5.1 The Eye (Candy) Exam.................................172
References.......................................................
Contents
XI
CHAPTER 9 The Data Visualization Continuum.......................177
9.1 Data Visualization Definition..........................178
9.2 The Power of Viz.......................................180
9.3 To Explain or Explore—Or Both?.........................183
9.3.1 Explanatory......................................183
9.3.2 Exploratory......................................184
9.3.3 The Hybrid Model.................................186
9.4 The Rise of the Infographic............................187
9.5 Choosing the Chart: A Quick Diagnostic.................188
9.6 Data Visualization Golden Rules........................193
9.6.1 Rule #1: Visualize with Goals in Mind............193
9.6.2 Rule #2: Know Your Data..........................194
9.6.3 Rule #3: Put Your Audience First.................195
9.6.4 Rule #4: Be Media Sensitive......................195
9.6.5 Rule #5: Choose the Right Chart..................195
9.6.6 Rule #6: Practice Responsible Charting...........196
9.6.7 Rule #7: Use Labels Wisely.......................197
9.6.8 Rule #8: Design with Care........................198
9.6.9 Rule #9: Let the Data Speak......................199
9.6.10 Rule #10: Edit and Revise Before You Share......199
9.7 Conclusions............................................200
References................................................ 200
PART III BUILDING THE FOUNDATION FOR DATA
VISUALIZATION___________________________________________________
CHAPTER 10 Architecting for Discovery-----------------------------203
10.1 Key Information Challenges for Data Discovery..........204
10.1.1 The Integration Challenge.......................204
10.1.2 The Management Challenge........................205
10.1.3 The Discovery Challenge.........................206
10.2 Tackling Today’s Information Challenges................207
10.2.1 Choosing Data Abstraction for Unification.......207
10.2.2 Centralizing Context in the Cloud...............209
10.2.3 Getting Visual with Self-Service................210
10.3 Designing for Frictionless.............................212
10.4 Enabling Governed Data Discovery.......................213
10.4.1 Governance Checkpoints in Discovery.............214
10.5 Conclusions............................................218
10.6 Anatomy of a Visual Discovery Application..............218
Contents
10.7 The Convergence of Visual Analytics and Visual Discovery.....219
References.........................................................^
CHAPTER 11 Data Visualization as a Core Competency..........................221
11.1 Data Visualization Business Benefits and Risks..............222
11.1.1 Benefits.............................................222
11.1.2 Risks...............................................223
11.2 Introducing the Data Visualization Competency Center........223
11.2.1 Decision Design Standards.............................225
11.2.2 Establish Internal Data Visualization Best Practices.226
11.2.3 Develop a Collaborative, Collective Culture..........227
11.2.4 A Brief Word on Mobile...............................228
11.3 Tools for the DVCC...........................................229
11.4 Socializing the DVCC........................................231
11.4.1 Crafting a Vision Statement...........................232
11.4.2 Building the Core Team..............................233
11.5 The Implementation Roadmap..................................234
11.5.1 Aligning Business Outcomes to Drivers
and Efficiencies.....................................235
11.5.2 Establishing Success Criteria for Each Phase........236
11.5.3 Identifying Quick Wins to Prove Value................237
11.5.4 Architecting an All-Inclusive Communication Plan.....237
11.6 Four Tips to DVCC Success....................................238
11.6.1 Take Time to Conduct Due Diligence....................239
11.6.2 Establish a Common Business Vocabulary..............239
11.6.3 Know Who Your Data Stewards are......................240
11.6.4 Respect the Limitations of Self-Service Visualization ...241
References.......................................................242
CHAPTER 12 Visual Discovery by Design.......................................243
12.1 Data Discovery by Design....................................244
12.1.1 Power of Disruption (in the Tool Landscape).........245
12.1.2 The Value of Speed..................................247
12.1.3 Discovery by Design.................................249
12.1.4 Tying it Together...................................252
12.2 Leveraging Visualization for Assessable, Meaningful,
Actionable................................................. 254
12.3 Three Key Points to a Useful Data Visualization.............255
Reference.......................
Contents
CHAPTER 13 The Need for Visualization in the Internet
of Things................................................257
13.1 Understanding “Data in Motion”...........................258
13.2 The Internet of Things Primer............................259
13.3 The Art of Animation.....................................261
13.3.1 Beyond Animation to Streaming Data Visualization..264
13.4 Human Centered Design in Mobile(First) Strategies........267
13.4.1 Wearable Devices..................................268
13.4.2 Wearables for Him/Her.............................271
13.4.3 Personal Visual Analytics.........................272
13.5 Interaction for Playful Data Visualization...............272
13.5.1 Gamification and Gameplay.........................275
13.5.2 Interactivity.....................................275
References.....................................................278
Appendix.................................................................281
Subject Index............................................................283
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| spelling | Ryan, Lindy Verfasser (DE-588)109933229X aut The visual imperative creating a visual culture of data discovery Lindy Ryan Amsterdam ; Boston ; Heidelberg ; London ; New York ; Oxford ; Paris ; San Diego ; San Francisco ; Singapore ; Sydney ; Tokyo Elsevier Morgan Kaufmann [2016] © 2016 XXVI, 293 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Business / Data processing Datenverarbeitung Wirtschaft Big Data (DE-588)4802620-7 gnd rswk-swf Visualisierung (DE-588)4188417-6 gnd rswk-swf Visualisierung (DE-588)4188417-6 s Big Data (DE-588)4802620-7 s DE-604 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028920992&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Ryan, Lindy The visual imperative creating a visual culture of data discovery Business / Data processing Datenverarbeitung Wirtschaft Big Data (DE-588)4802620-7 gnd Visualisierung (DE-588)4188417-6 gnd |
| subject_GND | (DE-588)4802620-7 (DE-588)4188417-6 |
| title | The visual imperative creating a visual culture of data discovery |
| title_auth | The visual imperative creating a visual culture of data discovery |
| title_exact_search | The visual imperative creating a visual culture of data discovery |
| title_full | The visual imperative creating a visual culture of data discovery Lindy Ryan |
| title_fullStr | The visual imperative creating a visual culture of data discovery Lindy Ryan |
| title_full_unstemmed | The visual imperative creating a visual culture of data discovery Lindy Ryan |
| title_short | The visual imperative |
| title_sort | the visual imperative creating a visual culture of data discovery |
| title_sub | creating a visual culture of data discovery |
| topic | Business / Data processing Datenverarbeitung Wirtschaft Big Data (DE-588)4802620-7 gnd Visualisierung (DE-588)4188417-6 gnd |
| topic_facet | Business / Data processing Datenverarbeitung Wirtschaft Big Data Visualisierung |
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