Strategic Analysis of Big Data in Rapid Transit

Transcription

1 Brochure More information from Strategic Analysis of Big Data in Rapid Transit 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 Aim The aim of this study is to evaluate the revenue growth opportunities available for big data in the rail industry. It identifies business cases and opportunities for future growth. Objectives - The study provides a strategic overview of the Big Data market possible business cases and approaches - To discuss potential opportunities within the rail industry and related case studies. - To provide an overview of the level of involvement of OEMs in this space. - To discuss strategic conclusions and recommendations. - It provides the market size and penetration forecast of big data in rail transportation spend from 2014 to Key Questions this Study will Answer: - What are the possible business Big Data can generate across the rail industry? - Why is Big Data important for the rail environment and where it can help in terms of features and services? - What are the current opportunities within the rail industry using Big Data and related, successful case studies? - What market dynamics are influencing the implementation of Big Data? Contents: 1. Executive Summary - Implications of Big Data - North America and Europe are the Largest Markets for Big Data - Key Findings and Future Outlook 2. Research Scope, Objectives, Background, and Methodology - Research Scope - Research Aims and Objectives - Key Questions This Study Will Answer - Research Background - Research Methodology 3. Definitions and Segmentation - Big Data Market Segmentation 4. Introduction to Big Data - Scale of Big Data is in Petabytes - Predictive Analysis is the Future iteration of Business Intelligence 5. Migration Strategy Towards Big Data - 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

2 6. Implications of Big Data on Rail - 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 7. Mega Trends and Industry Convergence Implications - 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 8. Drivers and Restraints - Market Drivers - Drivers Explained - Market Restraints - Restraints Explained 9. Forecast and Trends - Big Data in Rail - Revenue Forecast Scenario Analysis - Rail Big Data Market F&S By Component - Big Data Revenue By Source 10. Market Share and Competitive Analysis - 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 11. Case Studies - Union Pacific Big Data Case Study - Portland TriMet Pioneer In Embracing Data Visualization 12. Conclusions - The Last Word Three Big Predictions - Key Conclusions and Future Outlook 13. Appendix - Legal Disclaimer - Total Big Data Market By Component Market Engineering Methodology - Appendix Ordering: Order Online - Order by Fax - using the form below Order by Post - print the order form below and send to Research and Markets, Guinness Centre, Taylors Lane, Dublin 8,

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