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 ForManagement 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.
