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Building Analytics Teams

You're reading from   Building Analytics Teams Harnessing analytics and artificial intelligence for business improvement

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781800203167
Length 394 pages
Edition 1st Edition
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Author (1):
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John K. Thompson John K. Thompson
Author Profile Icon John K. Thompson
John K. Thompson
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Table of Contents (14) Chapters Close

Preface 1. Introduction 2. An Overview of Successful and High-Performing Analytics Teams FREE CHAPTER 3. Building an Analytics Team 4. Managing and Growing an Analytics Team 5. Leadership for Analytics Teams 6. Managing Executive Expectations 7. Ensuring Engagement with Business Professionals 8. Selecting Winning Projects 9. Operationalizing Analytics – How to Move from Projects to Production 10. Managing the New Analytical Ecosystem 11. The Future of Analytics – What Will We See Next? 12. Other Books You May Enjoy
13. Index

Team architecture/structure options

In my mind, most concepts exist on a continuum. Building a successful advanced analytics and AI team is typified by two approaches that inhabit the two poles of the relevant continuum – Artisanal or Factory:

Figure 2.1: Artisanal and Factory team structure comparison

The Artisanal team architecture/structure

Let's start with the Artisanal approach.

The Artisanal approach is where the data scientists are the owners, managers, experts, and driving force behind their projects.

The data scientists design and execute every step of the process. The data scientists engage with the project sponsors, the subject matter experts, internal and external consultants, syndicated data providers, and any other individual or group that has a role to play in the project.

Data scientists capable of executing and managing the artisanal approach possess exemplary communication skills, are open to listening to a wide range of...

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