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10 Big Data Analytics for Connected Vehicles and Smart Cities Introduction 11

catalog of transportation use cases that are relevant to a smart city. These will be
presented in a standard format that contains the following use case attributes:

• Smart city transportation service addressed;
• Use case name;
• Objectives;
• Expected outcome of analyses;
• Success criteria;
• Source data examples;
• Business benefits;
• Challenges;
• Analytics that can be applied.

This chapter will provide the reader with an explanation of how the tools
and techniques contained in the book can be applied to smart city transporta-
tion services. It also provides a logical structure that can form the basis for a use
case catalog for a smart city. A catalog is not intended to be a comprehensive
prescription but is a model on which to base thinking across the smart city.
This is designed to enable progress toward formalizing descriptions of what
big data and analytics will do. This is part of the what-how cycle, introduced
in this chapter. This progress involves an evolution of the knowledge of what is
required to address practical problems, in light of a growing understanding of
how it can be done.

Chapter 9
The concept of a data lake is used to communicate the creation of a central,
accessible, discoverable body of data. Chapter 9 discusses and explains a robust
approach to the creation of a data lake. The approach incorporates the pitfalls
and challenges encountered in previous projects with the creation of a data lake
and the lessons learned from those difficulties. It is not intended to be a one-
size-fits-all recipe for the creation of a data lake, but rather, a model from which
to build customized approaches for each implementation.

Chapter 10
Examples of the implementation of the techniques and concepts contained in
this book provide a powerful tool for explaining the relevance and usefulness of
the book’s contents. Ideally, the examples would represent a full implementa-