Page 6 - Building Big Data Applications

xiv Preface

success has been demonstrated. If you ever wondered what the foundational difference in
building a Big Data application is the foundational difference is that the datasets can be
harvested and an experimental stage can be repeated if all of the steps are documented and
implemented as specified into requirements. Any team that wants to become successful in
the new world needs to remember that we have to follow governance and implement
governance in order to become measurable. Measuring process completion is mandatory to
become successful and as you read it in the book revisit this point and draw the highlights
from.
In developing this book there are several discussions that I have had with teams from
both commercial enterprises as well as research organizations and thank all contributors for
that time and insights and sharing the endeavors, it did take time to ensure that all the
relevant people across these teams were sought out and tipping point of failure what dis-
cussed in order to understand the risks that could be identified and avoided in the journey.
There are several reference points that has been added to chapters and while the book is not
all encompassing by any means it does provide any team that wants to understand how to
build a Big Data application choices of how success can be accomplished as well as case
studies that vendors have shared showcasing how companies have implemented technolo-
gies to build the final solution.
I thank all vendors who provided material for the book and in particular IO-Tahoe,
Teradata, and Kinetica for access to teams to discuss the case studies.
I thank my entire editorial and publishing team at Elsevier publishing for their
continued support in this journey for their patience and support in ensuring completion of
this book is what is in your hands today.
Last but not the least, I thank my wife and our two sons for the continued inspiration
and motivation for me to write. Your love and support is a motivation.