Authors:
- Helps you debug why your team is failing or underperforming due to management issues
- Covers how to skill and resource data science, data engineering, and operations teams
- Teaches you how to assign the right task to the right team or correctly divide a task between different teams
- Shows you how the business should interact with the data teams to create the highest value possible
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Table of contents (19 chapters)
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Front Matter
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Introducing Data Teams
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Front Matter
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Building Your Data Team
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Front Matter
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Working Together and Managing Data Teams
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Front Matter
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Case Studies and Interviews
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Front Matter
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About this book
Learn how to run successful big data projects, how to resource your teams, and how the teams should work with each other to be cost effective. This book introduces the three teams necessary for successful projects, and what each team does.
Most organizations fail with big data projects and the failure is almost always blamed on the technologies used. To be successful, organizations need to focus on both technology and management.
Making use of data is a team sport. It takes different kinds of people with different skill sets all working together to get things done. In all but the smallest projects, people should be organized into multiple teams to reduce project failure and underperformance.
This book focuses on management. A few years ago, there was little to nothing written or talked about on the management of big data projects or teams. Data Teams shows why management failures are at the root of so many project failures and how to proactively prevent such failures with your project.
What You Will Learn
- Discover the three teams that you will need to be successful with big data
- Understand what a data scientist is and what a data science team does
- Understand what a data engineer is and what a data engineering team does
- Understand what an operations engineer is and what an operations team does
- Know how the teams and titles differ and why you need all three teams
- Recognize the role that the business plays in working with data teams and how the rest of the organization contributes to successful data projects
Who This Book Is For
Management, at all levels, including those who possess some technical ability and are about to embark on a big data project or have already started a big data project. It will be especially helpful for those who have projects whichmay be stuck and they do not know why, or who attended a conference or read about big data and are beginning their due diligence on what it will take to put a project in place.This book is also pertinent for leads or technical architects who are: on a team tasked by the business to figure out what it will take to start a project, in a project that is stuck, or need to determine whether there are non-technical problems affecting their project.
Authors and Affiliations
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Reno, USA
Jesse Anderson
About the author
Jesse Anderson serves in three roles at Big Data Institute: data engineer, creative engineer, and managing director. He works on big data with companies ranging from startups to Fortune 100 companies. His work includes training on cutting-edge technologies such as Apache's Kafka, Hadoop, and Spark. He has taught over 30,000 people the skills needed to become data engineers.
Jesse is widely regarded as an expert in the field and for his novel teaching practices. He has published for O’Reilly and Pragmatic Programmers. He has been covered in prestigious publications such as: The Wall Street Journal, CNN, BBC, NPR, Engadget, and Wired. He has spent the past 6+ years observing, mentoring, and working with data teams. He has condensed this knowledge of why teams succeed or fail into this book.
Bibliographic Information
Book Title: Data Teams
Book Subtitle: A Unified Management Model for Successful Data-Focused Teams
Authors: Jesse Anderson
DOI: https://doi.org/10.1007/978-1-4842-6228-3
Publisher: Apress Berkeley, CA
eBook Packages: Business and Management, Apress Access Books, Business and Management (R0)
Copyright Information: Jesse Anderson 2020
Softcover ISBN: 978-1-4842-6227-6Published: 19 September 2020
eBook ISBN: 978-1-4842-6228-3Published: 18 September 2020
Edition Number: 1
Number of Pages: XXIV, 294
Number of Illustrations: 13 b/w illustrations
Topics: Big Data