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
31-Dec-2014
REGION
Global
Global
Deliverable Type
Market Research
Market Research
Research Code: M9BA-01-00-00-00
SKU: TP00017-GL-MR_08688
$3,950.00
Special Price $2,962.50 save 25 %
In stock
SKU
TP00017-GL-MR_08688
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.
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
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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.
Deliverable Type | Market Research |
---|---|
No Index | Yes |
Podcast | No |
Author | Shyam Raman |
Industries | Transportation and Logistics |
WIP Number | M9BA-01-00-00-00 |
Is Prebook | No |