Big Data In Real Life

How Big Data is about more than boardrooms and increasing profits


Big Data has been cast as one of the biggest changes to businesses that we are likely to see in our lifetime. Undoubtedly, being able to look at everything your business is doing in minute detail is going to have a significant impact on performance, but what will it realistically change for the average person?

The truth is that Big Data is having a drastic affect on people’s day-to-day activities, but this largely flies under the radar as the business cases take centre stage.

So we have identified three uses for Big Data which are either currently having a major impact on your life or are likely to in the future.


As the world population is growing, infrastructure becomes more important and one of the biggest elements of this is how people move from one place to another.

London is a prime example of how it is done effectively despite the city’s levels of growth increasing year-on-year. To deal with this, Transport for London (TFL) have taken a data driven approach to running the train, bus and road network across England’s capital city.

Using the Oyster cards that were introduced in 2003, TFL have managed to log millions of different journeys, which has allowed them to be informed about the most popular routes or routes that could be faster. The necessity to log the start and end of a journey whilst using the train service has also meant that data surrounding where every journey is started and finished, the time of day and the duration of the journey help to inform TFL about ways to improve the service and direct people to the correct places.

It has also allowed a more personalized approach to reporting problems and finding solutions for them. In addition to being able to map mass movements, the data can help to pinpoint individuals who take particular routes and then help them find alternatives if there are disruptions or closures. Rather than simply reporting that certain areas will be affected, it means that the TFL can totally personalize the messages to make sure that those who are most likely to be disrupted are also the most informed.

Waste Management

Waste management is something that we do not appreciate until it stops working, it has a huge impact on the ability to have urban areas that do not end up spreading death and disease.

With the growing populations of urban areas, there needs to be a more considered and planned approach to managing the considerable amount of waste created. This is where Big Data is having a significant impact.

Greater Manchester Waste Disposal Authority (GMWDA) in the UK has been working with Manchester University to come up with innovative waste management solutions using the data they collect. This can be anything from the amount of waste collected from different areas to the amount that can be recycled or the frequency of collections. Without this kind of planning it would be impossible to effectively manage and would also be difficult to scale up given the increasing populations within these urban areas.

It is also helping to increase the levels of recycling, something that is becoming increasingly important as we move into a more sustainable age. In Manchester, for instance, they have monitored the weight of rubbish coming from different areas and used this information to incentivize recycling initiatives.

Weather Forecasting

We have become accustomed to inaccuracy in our weather forecasts, with each prediction taken with a pinch of salt. However, Big Data is changing this.

Through the use of increasingly complex and accurate sensors, combined with the ability to look at findings in real-time, then quickly push them out to relevant devices, the accuracy of these forecasts is constantly improving.

This was best shown by South Korea’s recent upgrade of its weather system following Typhoon Sanba’s destruction in 2012. The new IBM system gave them 1000 times more data storage and better accuracy when predicting weather. In fact using new Big Data techniques, an IBM team in New York can now predict how much rain will fall in a particular location 40 hours in advance with a 90% accuracy. It is still not perfect, but is having a significant impact on forecasts.

This use of data is helping to keep people safe whilst also allowing farmers and others who work outside to be able to work effectively and plan ahead with more certainty. 


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