Jeremy Adamson - Minding the Machines

1 Cover

2 Title Page Minding the Machines Building and Leading Data Science and Analytics Teams Jeremy Adamson

3 Foreword

4 Introduction

5 Chapter 1: Prologue For the Leader from the Business For the Career Transitioner For the Motivated Practitioner For the Student For the Analytics Leader Structure of This Book Why Is This Book Needed? Summary References

6 Chapter 2: Strategy The Role of Analytics in the Organization Current State Assessment Defining the Future State Closing the Gap References

7 Chapter 3: Process Project Planning Project Execution Summary References

8 Chapter 4: People Building the Team Leading the Team Summary References

9 Chapter 5: Future of Business Analytics AutoML and the No-Code Movement Data Science Is Dead The Data Warehouse True Operationalization Exogenous Data Edge AI Analytics for Good Analytics for Evil Ethics and Bias Analytics Talent Shortages Death of the Career Transitioner References

10 Chapter 6: Summary

11 Chapter 7: Coda

12 Index

13 Copyright

14 Dedication

15 About the Author

16 About the Technical Editor

17 About the Foreword Author

18 Acknowledgments

19 End User License Agreement

1 Chapter 2 Table 2.1: Capability model example

2 Chapter 3Table 3.1: The analytics project pipeline

1 Chapter 2Figure 2.1: Swimlane diagram of analytical interaction model

2 Chapter 4Figure 4.1: Needs pyramidFigure 4.2: Venn diagram showing strategy, people, and process for analytics ...

1 Cover Page

2 Table of Contents

3 Title Page Minding the Machines Building and Leading Data Science and Analytics Teams Jeremy Adamson

4 Copyright

5 Dedication

6 About the Author

7 About the Technical Editor

8 About the Foreword Author

9 Acknowledgments

10 Foreword

11 Introduction

12 Begin Reading

13 Index

14 WILEY END USER LICENSE AGREEMENT

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Jeremy Adamson

Data. There was a time when this word made reference to a Star Trek character or something professionals in the IT department who worked on databases would manage. Today data , data science , data engineering , data analysts , or any term including the use of data is pervasive across business, industries, and society. The use of the term data has practically become everyday vernacular in business; it seems to be the holy grail solution to everything. However, most organizations are still in the very early stages of their journey.

Many of the world's leading organizations can attribute their success to the fact that the practice of data science is increasingly becoming a strategic function. Analytics and data science enable consumer experiences that have become indispensable in our daily lives and deliver highly personalized recommendations and content, and this is now the expectation for almost everything else in our lives. The expectation of the customer has become immediate, personalized services that predict what it is they may want before they may even know it themselves. Data is what powers these great product experiences. Data science is no longer simply a technology function buried within IT or reserved purely for the tech giants in Silicon Valley. Data science and analytics will become increasingly indispensable in health care as it will improve diagnostic accuracy and efficiency. In finance, it will aid in the detection of anomalies and fraud. In manufacturing, it will aid in fault prediction and preventative maintenance. Whether you work in corporate strategy, research & insights, product development, human resources, marketing, technology, or finance, you will no longer be able to effectively compete without leveraging the talent and capabilities of the data science teams.

The need for knowledge in Data Science & Analytics, Algorithms & Artificial Intelligence is becoming evident in the sheer volume of online courses, degrees, and certifications available on EDx, Coursera, Udacity, and other online education providers. Top-ranked universities across Canada have introduced graduate degrees in data science and analytics. Two of the most prestigious universities in the world, the University of California, Berkeley, and Massachusetts Institute of Technology, are creating entirely new institutions within their campuses to come to terms with the ubiquity of data and the rise of artificial intelligence.