Page 203 - Big Data Analytics for Connected Vehicles and Smart Cities

184 Big Data Analytics for Connected Vehicles and Smart Cities Building a Data Lake 185

Improved Safety, Efficiency, and User Experience by Accelerating Analytics Work

There is often a significant time lag between smart city practitioners under-
standing the need for data analytics work and the work that has been put into
practice. The creation of the data lake and the number of self-service tools and
opportunities present their ability to parallel-stream work efforts and shorten
the time from realization of need to satisfaction of need with respect to data
analytics.

Better Data Governance with a Single Consistent Version of the Truth, Better Control
on Who, What and When Data Is Accessed or Provisioned
Bringing data together in a data lake allows better possibilities for data gover-
nance and configuration control. A single repository is much easier to manage
with respect to access control on data going into the lake and data analytics
emanating from the lake. A single repository also makes it easier to upgrade
software at a single point rather than at multiple points in a fragmented system.
Enabling Data Elements to Combine for New Analytics

The new big data approach to data storage and manipulation allows us to delay
judgment on the value of data. Data storage costs have reduced to the point
where a new strategy can be implemented. In simple terms this strategy involves
the capture of as much data as possible; the data will be ingested into the data
lake and then allowed to demonstrate its value. In this scenario, a seemingly
useless piece of data may combine with other data in the data lake to create
a new and valuable insight. There is a significant element of discovery that is
supported by the establishment of a data lake that would be unachievable in a
fragmented data storage and management approach.
Discovering Value in Unused Data and Relationships Between Data Sets Regarding
Customer Behavior and Transportation Service Delivery Quality
Building on the previous point, new value can be realized from data that has
either been hidden or unused within the overall smart city organization. Sunk
investment in data collection can be revitalized through the discovery of new
uses for the data. This also extends to the understanding of new relationships
between data sets. This is particularly relevant with respect to customer be-
havior and monitoring of transportation service delivery. Deeper insights into
how travelers behave and the prevailing transportation conditions they face will
ultimately lead to better strategies and tactics in the smart city.
Providing a Platform for Innovation in Smart Cities and Transportation
The use of analytics and big data techniques is only a small part of the overall
innovation that can be achieved by a smart city. However, the focused nature
of the work in creating a data lake can be used to propel the use of big data and