An introduction to big data and analytics and how they can improve the transportation industry
So, what’s big data all about?
Webopedia explains that the term denotes millions of gigabytes of data. Traditional data processing technologies will find it difficult to handle all the information.
For example, the first week of March saw over 503,017 carloads, containers, and trailers among U.S. rail traffic. This information becomes big data when you also consider the contents of each trailer and the real-time status of the goods. Everything related to the train, from its route to the last passenger who boarded or crate that was loaded, is taken into account.
Because the sets of information are so large, powerful computers can correlate different volumes of data to come up with useful insights. The example above may help rail companies in determining which routes are the most taxing for a passenger car, or how to prolong the time window for transporting perishable goods.
In fact, rail companies are catching up by installing sensors that record if a rail car has any wear and tear. Railway Age also details how big data is used for railroad inspection reports, which are crucial for predicting maintenance issues.
Big data used to be defined by the three V’s, which are volume, variety of data, and the velocity in which it can be processed. Today, variability (change in the range of values in a data set) and value (how important the data is) are often included. As more rail companies adopt cloud technology, one can expect big data to encompass not only these five V’s but also a wide range of data types that were once considered inconsequential. Such forms of information include even the tiniest details like how a railcar performed in a specific minute during a trip or how it’s affected when traversing a particular section of its route.
Analytics: Making sense of big data
The real value is extracted from big data through analytics. It’s the process of sifting through all of the information to make correlations, generate insights, and finalize business decisions. This is especially important in the so-called ‘Information Age’ where a comprehensive analytics strategy may provide a competitive edge.
The biggest challenge though is that analytics is resource-intensive and time-consuming. In our previous blog post, we mentioned that even companies with advanced data collection technology cannot hire enough people to do big data analytics. This is why most firms, especially smaller ones, outsource to third-party entities like CloudMoyo, which have dedicated tools and resources to do the job.
All things considered, big data and analytics have essentially become game-changers in different industries. And from this point on, they will only get more valuable as all sorts of information continue to be collated. Actually, Maryville University projects that 180 trillion gigabytes of data will be produced annually by 2025, and along with that there will be an increase in the demand for professionals to handle this data. These two technologies will continue to shape the world and how people experience it. And now is the best time to take advantage of their immense potential.
To learn more about how big data and analytics can benefit the sector, you may also check out Dataconomy’s article on the most recent innovations in AI and the rail industry. It explores how AI works in tandem with big data to improve Condition Based Maintenance (CBM) and Predictive Maintenance (PM).
Don’t forget to get in touch with us through our Contact page as well for more info on specific railroading solutions that use the same technologies.
This blog is contributed by Jesse Best