"For more than a decade, key decision-makers in the rail industry have been anticipating the next chapter of the Big Data era. This next phase will be defined by the ability to transform robust and disparate streams of raw data into actionable business insights in real-time.
Collecting vast amounts of data is a not a problem. Small network-enabled devices with sensors have been embedded in an increasing number of locomotives and rolling stock. However, infusing that raw data with context – thus turning it into actionable information that can optimize operations and drive new business opportunities – is still a significant challenge. One of the key problems is that the device- and data-management landscape for these transportation systems is ultimately siloed and difficult to manage.
The data nodes on each vehicle consist of hardware and software from a wide swath of manufacturers and service providers. Until now, much of the computing required for real-time data analysis has been done in the cloud, making these systems overly reliant on network connectivity."