The Role of Big Data in Improving Public Transport

TFL or Transport for London oversees a huge network of trains, buses, roads, footpaths, and ferries, used by millions of people every day. Running the vast network is crucial for TFL which gives it access to a large volume of data. It is gathered through ticketing systems and seasons linked it vehicles and traffic signals and social media. Madrid Software Trainings in association with industry experts provides complete practical Hadoop Training in Delhi Challenges in Managing the Travel Data!

The companies had two key priorities to collect and analyze this data which are planning services and providing information to customers. The population is expected to grow at a rapid rate. It takes planning to understand how to manage their transport needs.

It is a known fact that passengers always want good services and value for money. They want TFL to be innovative to meet their needs. There were prepaid travel cards that were first issued in 2003. Since then, these have been expanded across the network. Passengers charge them by converting real money from their accounts into TFL which are then swiped to gain access to trains and buses. As a result, it enables a large volume of data to be gathered about precise journeys which are being taken. In order to get a complete understanding of big data Hadoop technology, one can join Madrid Software Trainings which is considered the best Hadoop institute in Delhi by professionals.

Mapping the Journey!

This data is anonymized which is used for producing maps showing at the time and location of people traveling. It gives an accurate picture overall and allows granular analysis at individual journeys. When the London journeys encompass more than one way of transport, the level of analysis was not possible in the times when tickets were brought from various services in cash for each individual journey.

Traditionally tickets were bought from the driver for a set fee per journey. There was no mechanism for recording where a traveler leaves the bus and terminates their journey. In such a scenario, implementing the one was almost impossible without causing an inconvenience to the customer.

For rapid operation, data collection needs to be linked to business operations which were no less than a challenge for TFL. They worked with an academic institution to devise a Big Data solution for these problems. It inquired to look at where the next tap is because they are dealing with long journey using the bus. It helped to understand load profiles which mean how crowded a specific bus can be at a certain time. To plan interchange and to reduce walk time was a challenge.

Big Data analysis helped TLF to respond in an agile manner as and when disruption occurs. Then it was able to work out half of the journeys. The other half included crossing a nearby bridge at the half-way point of the journey. To serve their needs, they set up a transport interchange and enhance bus service on various alternate routes. The company was able to quantify people by using Big Data.

Personalizing the News by Using Technology!

Travel data is also used for identifying customers who take specific routes regularly and send tailored updates to them. If a customer uses a specific station frequently, the information is included about service changes at the station in their updates. It is understood that people are hit by a lot of data nowadays, so there is a strong focus on sending only relevant data.

The information from the back office systems is used for processing the contactless payments. TFL also offers its data through open APIs which is for use by 3rd party app developers. It means that customized solutions can also be developed for user groups. The system is currently run by various Microsoft and Oracle platforms. The organization is now looking into adopting Hadoop and various other open source solutions to overcome the increasing demands of data.

But Hadoop seems to be a great choice to cope up with growing data demands in future. Plans for the future also encompass increasing the capacity for real-time analytics and work on integrating a wide range of data sources to plan better and inform customers.

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Big Data has amazingly played a big part in re-energizing the transport network of London. It is evident that it has been implemented smartly as well. Big Data is indeed interesting but sometimes you require finding a business case. Managing such a huge network of transport would have been impossible for TFL without Hadoop. Therefore, it clearly reflects the power of big data which is nowadays helping leaders to overcome the challenges of managing the huge volume of data. for more information.

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