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182 Big Data Analytics for Connected Vehicles and Smart Cities Building a Data Lake 183

This indicates that the private sector may also have access to both data and
analytics from the data lake.

9.6 Value of a Data Lake

While the ultimate value of a data lake lies in providing support for smart city
services and the delivery of insight to smart city practitioners, there is a range
of benefits that are realized when a data lake is developed. These include the
following:

• Enterprise-wide data access for timely analytics and insights;
• The foundation for large-scale proactive analytics;
• A steppingstone toward automation through predictive analytics and
machine learning;
• Reduced costs due to data management duplication and processing
duplication;
• Improved safety, efficiency, and user experience by accelerating analytics
work;

• Better data governance with a single consistent version of the truth and
better control on who, what, and when data is accessed or provisioned;
• The ability of data elements to combine for new analytics;
• Discovering value in unused data and relationships between data sets
regarding customer behavior and transportation service delivery quality;
• Providing a platform for innovation in smart cities and transportation;
• Providing support for smart city service delivery.

Now we consider each of these in turn.

Enterprise-wide Data Access for Timely Analytics and Insights

While bringing the data together in creating the data lake, the data assets for
the smart city become visible. In addition to creating a data catalog that enables
all users to see the data that has been collected, the data is made available to a
wide range of users for further analysis. The analytics that have been derived
from processing data in the data lake can also be shared across the organization,
providing motivation and stimulus for further use of the data lake and develop-
ment of customized analytics for specific job functions such as transportation
planning, traffic engineering, and asset management.