Minding the machines : building and leading data science and analytics teams / Jeremy Adamson.

Format:

Book

Language:

English

Subjects (All):

Big data.

Quantitative research--Data processing.

Quantitative research -- Data processing.

Information technology.

Teams in the workplace--Data processing.

Teams in the workplace -- Data processing.

Leadership.

Physical Description:

1 online resource (205 pages)

Place of Publication:

Hoboken, N.J.: Wiley, c2021.

Summary:

Organize, plan, and build an exceptional data analytics team within your organization In Minding the Machines: Building and Leading Data Science and Analytics Teams, AI and analytics strategy expert Jeremy Adamson delivers an accessible and insightful roadmap to structuring and leading a successful analytics team. The book explores the tasks, strategies, methods, and frameworks necessary for an organization beginning their first foray into the analytics space or one that is rebooting its team for the umpteenth time in search of success. In this book, you'll discover: * A focus on the three pillars of strategy, process, and people and their role in the iterative and ongoing effort of building an analytics team * Repeated emphasis on three guiding principles followed by successful analytics teams: start early, go slow, and fully commit * The importance of creating clear goals and objectives when creating a new analytics unit in an organization Perfect for executives, managers, team leads, and other business leaders tasked with structuring and leading a successful analytics team, Minding the Machines is also an indispensable resource for data scientists and analysts who seek to better understand how their individual efforts fit into their team's overall results.

Contents:

Intro

Table of Contents

Title Page

Foreword

Introduction

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

Chapter 2: Strategy

The Role of Analytics in the Organization

Current State Assessment

Defining the Future State

Closing the Gap

Chapter 3: Process

Project Planning

Project Execution

Chapter 4: People

Building the Team

Leading the Team

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

Chapter 6: Summary

Chapter 7: Coda

Index

Copyright

Dedication

About the Author

About the Technical Editor

About the Foreword Author

Acknowledgments

End User License Agreement.

Notes:

Includes bibliographical references and index

Includes bibliographical references and index.

ISBN:

1-119-78533-2

1-119-78534-0

OCLC:

1259590484