Winning with Data

Transform Your Culture, Empower Your People, and Shape the Future
(176 Seiten)
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Tomasz Tunguz
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Crest the data wave with a deep cultural shift
Winning with Data explores the cultural changes big data brings to business, and shows you how to adapt your organization to leverage data to maximum effect. Authors Tomasz Tunguz and Frank Bien draw on extensive background in big data, business intelligence, and business strategy to provide a blueprint for companies looking to move head-on into the data wave. Instrumentation is discussed in detail, but the core of the change is in the culture--this book provides sound guidance on building the type of organizational culture that creates and leverages data daily, in every aspect of the business. Real-world examples illustrate these important concepts at work: you'll learn how data helped Warby-Parker disrupt a $13 billion monopolized market, how ThredUp uses data to process more than 20 thousand items of clothing every day, how Venmo leverages data to build better products, how HubSpot empowers their salespeople to be more productive, and more. From decision making and strategy to shipping and sales, this book shows you how data makes better business.

Big data has taken on buzzword status, but there is little real guidance for companies seeking everyday business data solutions. This book takes a deeper look at big data in business, and shows you how to shift internal culture ahead of the curve.
* Understand the changes a data culture brings to companies
* Instrument your company for maximum benefit
* Utilize data to optimize every aspect of your business
* Improve decision making and transform business strategy

Big data is becoming the number-one topic in business, yet no one is asking the right questions. Leveraging the full power of data requires more than good IT--organization-wide buy-in is essential for long-term success. Winning with Data is the expert guide to making data work for your business, and your needs.
Introduction ix

Chapter 1 Mad Men to Math Men: The Power of the Data-Driven Culture 1

Operationalizing Data: Uber's Competitive Weapon 2

The Era of Instant Data: You Better Get Yourself Together 4

Data Supply Chains: Buckling Under the Load 6

Management by Opinion: The Illusion of Knowledge 8

Our Vantage Points 10

Chapter 2 Four Problems with Data Today: Breadlines, Obscurity, Fragmentation, and Brawls 15

Data Breadlines for the Data-Poor 15

Data Obscurity: The Failure of the Card Catalog 17

Rogue Databases and Analysts: The Data Fragmentation Problem 19

Data Brawls: When Miscommunication Devolves into Arguments 21

Chapter 3 Business Intelligence: How We Got Here 23

Business Intelligence Is Born: The First Query 23

Databases for the Masses: Oracle Commercializes Codd's Invention 24

Legacy BI: A Three-Layer Cake 26

Google's Answer to Huge Data: Vanilla Boxes 27

600 Petabytes per Day: HiPal at Facebook 30

Extreme Data Collection: The New Normal 32

Looker: Weaving the Data Fabric 33

Chapter 4 Achieving Data Enlightenment: Gathering Data in the Morning and Changing Your Business's Operations in the Afternoon 37

Not Just Another Person with an Opinion 37

Aligning Sales Teams in Real Time 48

Scaling Sales Teams with Data 50

Determining Customer Satisfaction at Every Point in the Buyer Journey 52

The Rosetta Stone: Developing a Shared Data Language 55

The One Equation That Defines the Business 57

Brutal Intellectual Honesty: Speaking Data to Power 60

Putting Pride in Its Place: How Data Transforms Cultures 66

Chapter 5 Five Steps to Creating a Data-Driven Company--From Recruiting to Regression, It All Starts with Curiosity: Changing the Culture 71

It All Starts with Curiosity 71

Why You Should Stop Listening to Your Boss 72

How to Recruit Curious People 76

Chapter 6 From Hacks to Harmony: The Typical Progression of Data-Driven Companies 83

Step 1: Ask Your Friend, the Engineer 84

Step 2: Bastardize an Existing Solution 84

Step 3: Access Raw Data 85

The Crux of the Problem 85

Bring Your Own BI: The Five Letters That Will Change the Data World 86

The Power of a Unified Data-Modeling Layer 89

The Final Step: A Data Fabric 92

Chapter 7 Data Literacy and Empowerment: The Core Responsibilities of the Data Team 95

The Illusion of Validity: How to Avoid Data Biases 95

Correlation versus Causation 98

How Facebook and Zendesk Engender Data Literacy 100

Walking the Data Gemba: Training by Walking Around 104

Chapter 8 Deeper Analyses: Asking the Right Questions 109

When Data Confounds Our Intuition: How to Handle Ambiguity 112

Data Is Useless Unless You Can Act on It 115

Defining New Opportunities by Creating New Metrics That Matter 120

The Fastest Growing Media Site of All Time 122

How to Run a Data-Backed Experiment: Step by Step 124

Chapter 9 Changing the Way We Operate 129

Change Begins with a Story 129

Deliver Data with Panache: Structuring Presentations to Inspire 133

Chapter 10 Putting It All Together 141

Acknowledgments 145

Appendix: Revenue Metrics 147

Index 155

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