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276 Big Data Analytics for Connected Vehicles and Smart Cities Summary 277

tween reporting and analytics—that analytics tend to span multiple data sourc-
es and are more likely to consist of ratios and comparisons between different
data elements. Analytics also provides a more flexible approach that can answer
the questions you have already identified and ones that you will discover in the
process of using big data and analytics. The conventional KPI and reporting ap-
proach tends to create a rigid framework that has difficulty in accommodating
new questions. Chapter 6 also provides an important differentiator in the form
of a sporting analogy suggesting that even the best reporting system can only
make you a spectator at a sports game. Data analytics are an essential tool to
enable you to become the coach and exert an influence over the performance of
the team or the organization. Accordingly, Chapter 6 further explores the value
of analytics by explaining the key role that they play in uncovering patterns and
trends within smart city transportation. In addition, Chapter 6 lists analytics
for each of the smart city transportation services previously identified, provid-
ing concrete examples of their direct relevance to smart city transportation.

12.10 Review of Chapter 7

Building on the concept of a departure point in steppingstones for smart city
evolution, Chapter 7 identifies five possible departure points for a smart city
from a transportation perspective. Each of the departure points is examined
in terms of the overall nature of the departure point, its suitability as a depar-
ture point, and the type of analytics that can be used to support the deploy-
ment of the departure point. This approach enables the practical application of
smart city transportation analytics to be couched within a possible approach
to defining starting points and roadmaps for smart city transportation service
evolution. While Chapter 7 does not provide a comprehensive list of possible
departure points and only explains a sample of the relevant analytics, it should
be sufficient to provide the basis for a customized approach to transportation
analytics and service evolution within a smart city.

12.11 Review of Chapter 8

A system engineering tool known as the use case has a disproportionately im-
portant role in the bridge between transportation and data science. For trans-
portation professionals within a smart city, the use case captures the problems
to be addressed, the analytics to be applied, the data required, and the benefits
that will be achieved. From a data science point of view this is essential commu-
nication of the customer needs, issues, problems, and objectives, that are vital
in guiding the development of big data and analytics approaches. Accordingly,
Chapter 8 defines the term use case and provides some examples of smart city