Big Data in the Transportation Industry

BIG DATA 1
Big Data
Student Name
Institutional Affiliation
Date

BIG DATA 2
Executive Summary
Big data have been employed in different use case including the transportation
industry. Big data technologies have had a significant impact on the various aspects in the
transport companies like Uber. Uber can leverage big data techniques to improve their
interaction with their partners and clients by pinpointing the new patterns emerging in the
industry and react by providing new products. Also, the company can employ big data tools
to bargain charges with suppliers, increase the income of each operation and reveal unseen
opportunities and this also applies to Uber. Generally, the transport industry can also use big
data approaches to create intelligent transportation system using toll data and vehicle
counting data to predict traffic conditions on the road. This enables travel companies like
Uber to make more informed decisions and choose the best routes with less traffic and ensure
that their clients have reached their destination on time.
This report has described how big data can by Uber by describing the various big data
technologies and tools with their strengths and limitations. The report has also proposed an
architectural solution for Uber which will use Apache Spark, MongoDB, and DATEX-II
standard for data harmonization. As such, the report has concluded by recommending on the
need for Uber to adopt big data and analytics to correctly model and improve capacity,
pricing, revenue, demand, schedules, customer sentiment, cost, among others. Utilization of
big data will enable Uber to significantly enhance the client experience, make the best use of
the available infrastructure and assets, improve services to manage capacity and maximize
revenue, and optimize operational effectiveness.

BIG DATA 3
Table of Contents
Executive Summary...................................................................................................................2
Introduction................................................................................................................................4
Big Data Use Cases....................................................................................................................4
Customer Analytics and Loyalty Marketing..........................................................................4
Capacity and Pricing Optimization........................................................................................6
Predictive Maintenance Analytics..........................................................................................7
Big Data Technologies...............................................................................................................9
Apache Hadoop......................................................................................................................9
Apache Spark.......................................................................................................................10
Data lakes.............................................................................................................................10
NoSQL (MongoDB).............................................................................................................11
Apache Cassandra................................................................................................................11
Big Data Architecture Solution................................................................................................12
Conclusion................................................................................................................................15
List of References....................................................................................................................17

BIG DATA 4
Introduction
Big data is helping travel companies understand the travel choice and behavior of a
passenger as well as gaining insights on the performance of the industry as a whole. Uber can
make use of big data in their strategic pricing and revenue management which allow them to
provide excellent travel experiences to their customers and maximize their revenue
opportunities. Additionally, Uber can leverage big data tools to optimize their network
connectivity according to market needs. By utilizing big data tools, Uber can pinpoint the
new patterns emerging in the industry and react by providing new products. Big data tools
permit travel agents to bargain charges with suppliers, increase the income of each operation
and reveal unseen opportunities and this also applies to Uber (Riahi and Riahi, 2018).
Business analytics allows travel companies such as Uber to gain insight about the current
demand for brands and as a result, predict the supply and demand position. The context will
discuss the different Uber big data uses cases, critically analyze the big data technologies and
illustrate the big data architecture solution.
Big Data Use Cases
Based on the big data strategy developed in assessment 2, this section will describe
three major big data use cases that can provide positive business results to Uber. They
include:
Customer Analytics and Loyalty Marketing
Leaders of travel and transportation are dedicated to enhancing the experience of a
customer while improving marketing expenditure, customer service, and wallet share. By
securing data from client communications and other sources, Uber can acquire all important
and available data about a client to offer effective and most personalized client
service (Andonova, 2013). Apart from disclosing strategic knowledge into the purchasing
patterns of a customer, the all-round view assists in providing directly involved, client-facing
workers with the correct information to provide the best customer experience. They are well
prepared to effectively engage clients in relevant and personalized ways and to gain insights
from the previous client interactions, establishing reliable relationships and consistent
customer history.