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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

Personal project portfolio

Junior data scientists will likely come from the intern and co-op participant pool. Hiring people for full-time roles who have spent time with the analytics team and have been exposed to the broader organization is a much better way to hire full-time staff as compared to the traditional hiring process, especially in such a heated and frothy market as the data science market is today and looks to be in the foreseeable future.

If junior staff members do come from the intern and co-op participant ranks, then you understand their hard and soft skills and you know what they can and cannot do well. You, and they, understand the team dynamics and type of work and the cadence that is expected from them and the team. The ramp-up time to productivity is shorter and less time-consuming.

Junior members of the advanced analytics and AI team should be expected to undertake one main project and one or two service requests, to engage with the Community of Practice...

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