Exploit the power and potential of Big Data to revolutionize
business outcomes
Big Data Revolution is a guide to improving performance,
making better decisions, and transforming business through the
effective use of Big Data. In this collaborative work by an IBM
Vice President of Big Data Products and an Oxford Research Fellow,
this book presents inside stories that demonstrate the power and
potential of Big Data within the business realm. Readers are guided
through tried-and-true methodologies for getting more out of data,
and using it to the utmost advantage. This book describes the major
trends emerging in the field, the pitfalls and triumphs being
experienced, and the many considerations surrounding Big Data, all
while guiding readers toward better decision making from the
perspective of a data scientist.
Companies are generating data faster than ever before, and
managing that data has become a major challenge. With the right
strategy, Big Data can be a powerful tool for creating effective
business solutions – but deep understanding is key when
applying it to individual business needs. Big Data
Revolution provides the insight executives need to incorporate
Big Data into a better business strategy, improving outcomes with
innovation and efficient use of technology.
* Examine the major emerging patterns in Big Data
* Consider the debate surrounding the ethical use of data
* Recognize patterns and improve personal and organizational
performance
* Make more informed decisions with quantifiable results
In an information society, it is becoming increasingly important
to make sense of data in an economically viable way. It can drive
new revenue streams and give companies a competitive advantage,
providing a way forward for businesses navigating an increasingly
complex marketplace. Big Data Revolution provides expert
insight on the tool that can revolutionize industries.
Table des matières
Prologue 1
Introduction 7
PART I: THE REVOLUTION STARTS NOW: 9 INDUSTRIES TRANSFORMING WITH DATA 15
Chapter 1: Transforming Farms with Data 17
Chapter 2: Why Doctors Will Have Math Degrees 31
Chapter 3: Revolutionizing Insurance: Why Actuaries Will Become Data Scientists 45
Chapter 4: Personalizing Retail and Fashion 59
Chapter 5: Transforming Customer Relationships with Data 69
Chapter 6: Intelligent Machines 79
Chapter 7: Government and Society 89
Chapter 8: Corporate Sustainability 107
Chapter 9: Weather and Energy 119
PART II: LEARNING FROM PATTERNS IN BIG DATA 131
Chapter 10: Pattern Recognition 133
Chapter 11: Why Patterns in Big Data Have Emerged 141
Chapter 12: Patterns in Big Data 153
PART III: LEADING THE REVOLUTION 171
Chapter 13: The Data Opportunity 173
Chapter 14: Porsche 177
Chapter 15: Puma 181
Chapter 16: A Methodology for Applying Big Data Patterns 185
Chapter 17: Big Data Architecture 205
Chapter 18: Business View Reference Architecture 215
Chapter 19: Logical View Reference Architecture 223
Chapter 20: The Architecture of the Future 233
Epilogue 249
INDEX 255
A propos de l’auteur
Rob Thomas is Vice President of Product Development for Big Data and Information Management in IBM Software Group. Previously, he had responsibility for global sales and mergers & acquisitions. Patrick Mc Sharry is a Senior Research Fellow at the Smith School of Enterprise and the Environment, Faculty Member of the Oxford Man Institute of Quantitative Finance at Oxford University and Visiting Professor at the Department of Electrical and Computer Engineering, Carnegie Mellon University.
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