Big Data is very much at the top of the IT agenda at present. In fact, mobile computing aside, it’s hard to think of another area of IT creating as much hype. Not least because of how quickly the market for applications to collect, process and analyse Big Data stores is growing – with analyst firm IDC, for example, predicting global revenues of $32.4 billion by 2017.
Put another way, analysts like IDC are predicting a compound annual growth rate of over 25% – roughly six times that expected for IT in general.
But it’s not all about industry hype and projections. Customer demand is what’s really driving growth in this market, as companies strive to make better use of data collected and held by their organisations – to more effectively target sales and marketing efforts; improve products, services and the customer experience; deliver operating efficiencies and more.
The long term benefits of Big Data analysis are clear: Improved insight gained by identifying trends and synergies in data can deliver a much more complete view of a business and its customers and that, in turn, empowers companies to do things better.
Do it quickly and it can also deliver immediate benefits, giving companies the ability to react to changes in demand and rapidly tailor services and products to cope. To unlock and exploit Big Data in real-time, however, requires a lot more than tools to simply search and analyse the information being collected. It also calls for a robust and scalable communication infrastructure able to collect, interpret and act upon huge amounts of unstructured information in as little time as possible. If you like, it needs Fast Data.
An example will help put this into context, illustrating how one company – the Swiss Federal Railway – is using Fast Data to both improve customer satisfaction and do even more with its, already, highly efficient, railway network.
Known locally as Schweizerische Bundesbahnen (SBB) the company moves 350 million passengers and almost 50 million tons of freight every year on a rail network that packs 80 miles of track into every 600 square miles of land. Expansion is severely restricted due to topographical and financial constraints so, for some years now, the only way for SBB to increase capacity has been through improved efficiency.
Simply put – to get better, SBB has to run more trains, closer together, on the same track. To achieve that goal the company turned to the vast amount of data it captured every day and found ways to use that data to its advantage.
The company created a low-latency messaging system able to relay huge amounts of information back to its Rail Control System (RCS) for processing and action in real-time. Up to 1.7 terabytes of data are routed by the system every day, pulled from stations, passengers, trains and the network itself, enabling SBB to react in seconds as stock moves around the rail network to significantly enhance scheduling and improve punctuality.
For SBB, its passengers and customers whose freight is carried by the Swiss rail network, the benefits are compelling. Dispatchers are able to detect conflicts and reroute trains more quickly, which means timetables can be denser and traffic forecasts more accurate. The network is used more efficiently; more passengers and freight can be carried and customer satisfaction is rising.
There’s a cost advantage to be had from this use of Fast Data too, reduced staffing levels alone leading to annual savings of $3-4 million. Added to which by analysing usage patterns and training drivers to operate their trains more efficiently the rail operator expects to make energy savings of $10m per year.
What this example shows is that while Big Data is all the rage at the moment, it’s not just the amount of data that matters. Businesses need to collect, analyse and act on that data quickly which, in the case of SBB, means in real-time using messaging technology capable of processing large amounts of complex information with minimal latency and delay.
An extreme example, perhaps, but others can also benefit from this 21st Century technology and, by looking to continuously process and analyse Big Data in real-time, gain instant awareness and take instant action when needed. Other businesses can be equally empowered to do things better and, just like the Swiss Federal Railway, be on time with real-time Fast Data.