Data Teams
A Unified Management Model for Successful Data-Focused Teams
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Beschreibung
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.
You will:
- 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
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.
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
Autor*in
Jesse Anderson
Themen in »Data Teams«
data Big Data Data Science Data Scientist Data Engineering Data Engineer DataOps DataOps Engineer