Reasons to buy:
Procure strategically important competitor information, analysis, and insights to formulate effective R&D strategies.
Recognize emerging players with potentially strong product portfolio and create effective counter-strategies to gain competitive advantage.
Classify potential new clients or partners in the target demographic.
Develop tactical initiatives by understanding the focus areas of leading companies.
Plan mergers and acquisitions meritoriously by identifying Top Manufacturer.
Formulate corrective measures for pipeline projects by understanding Track Inspection Car pipeline depth.
Develop and design in-licensing and out-licensing strategies by identifying prospective partners with the most attractive projects to enhance and expand business potential and Scope.
[1], the University of Delaware’s annual “Big Data in Railroad Maintenance Planning” conference provides a forum for railroad and data analytics professionals to come together with academia and discuss the latest applications and research in railway-related data science. Clearly evident from these annual conferences, there is growing use of data analytics, often referred to as “Big Data,” to address maintenance and safety issues in all aspects of railroading: Engineering (Track and Structures), Equipment (Rolling Stock) and Transportation (Operations). This article will continue that discussion of the December 2020 conference, focusing on the Track and Right-of-Way-related applications of data analytics to the issues of railroad safety and maintenance. Although held in a virtual format, the conference organized by Drs. Allan M. Zarembski, Nii Attoh-Okine and Joseph Palese was able to attract more than 270 attendees from the full spectrum of railroad Big Data-related activit