Strategic Analysis of Big Data in Rapid Transit

Strategic Analysis of Big Data in Rapid Transit

Strategies to Achieve Predictive Analytics Biggest Driver for Big Data Implementation in Rail

RELEASE DATE
31-Dec-2014
REGION
Global
Research Code: M9BA-01-00-00-00
SKU: TP00017-GL-MR_08688
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Description

The strategic insight provides an outlook of growth opportunities in the Global rail market for Big Data. Secondary and primary research was conducted, including interviews with suppliers, regulation authorities, and distributors. The study discusses key trends, market drivers, opportunities, market size, and forecast of rolling stock deliveries for the rail industry It also highlights competitive factors, competitor market shares, product portfolio, and capabilities for this region. Key conclusions and a future outlook of the market have been provided. The base year is 2014; the forecast period is through 2021.

Table of Contents

Executive Summary—Key Findings

Implications of Big Data

North America and Europe are the Largest Markets for Big Data

Key Findings and Future Outlook

Research Scope

Research Aims and Objectives

Key Questions This Study Will Answer

Research Background

Research Methodology

Big Data Market—Segmentation

Introduction to Big Data

Scale of Big Data is in Petabytes

Predictive Analysis is the Future iteration of Business Intelligence

Incremental Big Data Implementation has Least Risk to Obsolescence

Hadoop is Quickly Becoming the Standard Core of Big Data

NoSQL is Key to Handling and Managing Social and Media Content

Media Analytics Open New Pathways to Predictive Analytics

Predictive Analytics is the Most important Implication of Big Data

Predictive Analytics from Big Data Requires Dedicated new Job Roles

Performance Improvement Possibilities with Predictive Analytics

Examples of Big Data Applications in the Rail Environment

Big Data Application—Demand Modeling and Ridership Forecasting

Big Data Application —Automated Train Operation

Big Data Application—Route Planning and Scheduling

Big Data Application—Automatic Vehicle Location

Big Data Application—Automated Fare Collection and E-Ticketing

Big Data Application—Advanced Lead Ranking and Conversion

Impact of Top 4 Mega Trends on the Turkish Rail Market

Impact of Top 4 Mega Trends on the Rail Big Data Market

Impact of Top 4 Mega Trends on the Turkish Rail Market (continued)

Market Drivers

Drivers Explained

Market Restraints

Restraints Explained

Revenue Forecast Scenario Analysis

Rail Big Data Market F&S By Component

Big Data Revenue By Source

IBM, HP and Dell worlds leading suppliers of Big Data Solutions

Top 20 Big Data Suppliers—Estimated Revenue from Big Data

Pure Big Data Technology Suppliers—Estimated Annual Revenue

Union Pacific Big Data Case Study

Portland TriMet Pioneer In Embracing Data Visualization

The Last Word—Three Big Predictions

Key Conclusions and Future Outlook

Legal Disclaimer

Total Big Data Market By Component 2014–2021

Market Engineering Methodology

Related Research
The strategic insight provides an outlook of growth opportunities in the Global rail market for Big Data. Secondary and primary research was conducted, including interviews with suppliers, regulation authorities, and distributors. The study discusses key trends, market drivers, opportunities, market size, and forecast of rolling stock deliveries for the rail industry It also highlights competitive factors, competitor market shares, product portfolio, and capabilities for this region. Key conclusions and a future outlook of the market have been provided. The base year is 2014; the forecast period is through 2021.
More Information
No Index Yes
Podcast No
Author Shyam Raman
Industries Transportation and Logistics
WIP Number M9BA-01-00-00-00
Is Prebook No