Big Data & Analytics Heroes
Phillippe Chartier, information delivery team lead at Canadian National Railway and this week's Big Data & Analytics Hero, tells us how they used to rely on monthly data reports, but now they operate more efficiently—in near real time—with predictive analytics. Canadian national Railway applies logical insights from their data to save fuel consumption, predict shipments and keep their trains running on time.
What "gold nuggets" have you uncovered using big data and analytics?
Canadian National Railway is the largest railway company in North America. We have the network from coast to coast in Canada and also from Chicago to New Orleans. We are focused on precision railroading. We’re doing a lot of analytics…getting more and more information from which we can get different insights. We have a project (fuel productivity) where they look at all different trains on the same area on the same track, and then they can start to compare what’s the best way to drive the train and reduce fuel consumption. Already in the last two years they managed to save millions of dollars.
How have big data and analytics impacted how you do your job today?
We’ve been using PureData for Analytics for five or six years now. Most queries for the reports that we have are running in maybe less than five seconds, where, previously, with other databases, we had some that were running for 10 to 20 minutes. We used to have reports that were monthly and now we’re moving towards almost real-time. Our users like it because we have a lot of data and the performance is very good with everything that we move to PureData.
How are big data and analytics changing your business strategy?
More and more we’re becoming like a logistic company, a supply chain enabler for our customers. We work to predict exactly where the trains will be and to be much more precise, delivering customers insights on when they will get their shipments and when they will get their rail cars. So, now, we’re doing much more of what we call precision railroading.
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