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The Decision Maker's Handbook to Data Science

A Guide for Non-Technical Executives, Managers, and Founders

  • Stylianos Kampakis
Book

Table of contents

  1. Front Matter
    Pages i-viii
  2. Stylianos Kampakis
    Pages 23-29
  3. Stylianos Kampakis
    Pages 31-43
  4. Stylianos Kampakis
    Pages 45-49
  5. Stylianos Kampakis
    Pages 59-75
  6. Stylianos Kampakis
    Pages 77-88
  7. Stylianos Kampakis
    Pages 89-95
  8. Stylianos Kampakis
    Pages 97-103
  9. Stylianos Kampakis
    Pages 105-123
  10. Stylianos Kampakis
    Pages 125-141
  11. Stylianos Kampakis
    Pages 143-144
  12. Back Matter
    Pages 145-156

About this book

Introduction

Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many don’t realize is that data science is in fact quite multidisciplinary—useful in the hands of business analysts, communications strategists, designers, and more.

With the second edition of The Decision Maker’s Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists

Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Maker’s Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide.

Keywords

Data analytics explained How to use machine learning in business Types of machine learning Data strategy Data culture Data science for managers Data science for executives How to hire data scientists ML vs AI Data science Data science made easy

Authors and affiliations

  • Stylianos Kampakis
    • 1
  1. 1.LondonUK

Bibliographic information

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