Rail Visibility: Connecting the Data

Multi source, multi-purpose, multi-ROI.  Data.  It's the new unwieldy business beast in the rail industry, and far more complex than some of the big boys of the day.  The countless applications, many sources, storage and integration for possible use cases create an intimidating landscape.  In this brief, we are simplifying the systems and process to make it a cohesive resource for Rail Operators and Rail Shippers. 

Regardless of the data source or hardware deployed, data analytics across multiple systems is one of the greatest opportunities for cost-savings facing the rail industry today.  Swedish researchers noted that railroads are "especially amenable to the advantages of Analytics and Big Data because they are generally closed systems that involve sophisticated processing of large volumes of data."

Current systems offering data for analysis include: 

» Geographic positioning system (GPS) devices
» Mobile and stationary assets
» Weather and census data from government resources
» Radio-Frequency Identification (RFID) systems
» Car Location Message (CLM) systems
» Track and facility data

And collectively these systems can produce substantial synergistic results.  In the brief "Connecting the Data," we break down initial steps and provide some current examples of deployment for shippers and operators.  Operations may find that simple executable tactics such as geo-fences combined with maintenance yards can reduce asset downtime substantially.  Shippers can reduce dwell time and enhance ride quality with adaptive configuration settings. 

And the next level of data integration is only a few steps further.  Data science, or the interdisciplinary field of, uses scientific methods, algorithms, processes, and systems to extract knowledge and insights from data in various forms; similar to data mining. In rail applications, many opportunities exist for data analysis.