Ulrika Jagare

Data Science Strategy for Dummies

• Broschiertes Buch

Produktbeschreibung

All the answers to your data science questions

Over half of all businesses are using data science to generate insights and value from big data. How are they doing it? Data Science Strategy For Dummies answers all your questions about how to build a data science capability from scratch, starting with the "what" and the "why" of data science and covering what it takes to lead and nurture a top-notch team of data scientists.

With this book, you'll learn how to incorporate data science as a strategic function into any business, large or small. Find solutions to your real-life challenges as you uncover the stories and value hidden within data.
_ Learn exactly what data science is and why it's important
_ Adopt a data-driven mindset as the foundation to success
_ Understand the processes and common roadblocks behind data science
_ Keep your data science program focused on generating business value
_ Nurture a top-quality data science team

In non-technical language, Data Science Strategy For Dummies outlines new perspectives and strategies to effectively lead analytics and data science functions to create real value.

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Produktdetails

• Verlag: For Dummies / Wiley & Sons
• Artikelnr. des Verlages: 1W119566250
• 1. Auflage
• Seitenzahl: 352
• Erscheinungstermin: 11. Juli 2019
• Englisch
• Abmessung: 233mm x 190mm x 20mm
• Gewicht: 658g
• ISBN-13: 9781119566250
• ISBN-10: 1119566258
• Artikelnr.: 54802444

Autorenporträt

Ulrika Jägare is an M.Sc. Director at Ericsson AB. With a decade of experience in analytics and machine intelligence and 19 years in telecommunications, she has held leadership positions in R&D and product management. Ulrika was key to the Ericsson??s Machine Intelligence strategy and the recent Ericsson Operations Engine launch ? a new data and AI driven operational model for Network Operations in telecommunications.

Inhaltsangabe

Foreword xv

Introduction 1

Part 1: Optimizing Your Data Science Investment 7

Chapter 1: Framing Data Science Strategy 9

Chapter 2: Considering the Inherent Complexity in Data Science 31

Chapter 3: Dealing with Difficult Challenges 41

Chapter 4: Managing Change in Data Science 51

Part 2: Making Strategic Choices for Your Data 65

Chapter 5: Understanding the Past, Present, and Future of Data 67

Chapter 6: Knowing Your Data 85

Chapter 7: Considering the Ethical Aspects of Data Science 97

Chapter 8: Becoming Data-driven 103

Chapter 9: Evolving from Data-driven to Machine-driven 113

Part 3: Building a Successful Data Science Organization 119

Chapter 10: Building Successful Data Science Teams 121

Chapter 11: Approaching a Data Science Organizational Setup 133

Chapter 12: Positioning the Role of the Chief Data Officer (CDO) 145

Chapter 13: Acquiring Resources and Competencies 155

Part 4: Investing in the Right Infrastructure 173

Chapter 14: Developing a Data Architecture 175

Chapter 15: Focusing Data Governance on the Right Aspects 193

Chapter 16: Managing Models During Development and Production 203

Chapter 17: Exploring the Importance of Open Source 213

Chapter 18: Realizing the Infrastructure 223

Part 5: Data as a Business 233

Chapter 19: Investing in Data as a Business 235

Chapter 20: Using Data for Insights or Commercial Opportunities 243

Chapter 21: Engaging Differently with Your Customers 255

Chapter 22: Introducing Data-driven Business Models 265

Chapter 23: Handling New Delivery Models 281

Part 6: The Part of Tens 295

Chapter 24: Ten Reasons to Develop a Data Science Strategy 297

Chapter 25: Ten Mistakes to Avoid When Investing in Data Science 305

Index 315