Read the Stories that Reveal the Value of Data

How do the workers in Distrito Telefónica move? The global Telefónica environment is designing a plan of sustainable movement for Distrito Telefónica. Data scientists of Big Data for Social Good from LUCA came together, supporting the analysis of data which provides objective understandingof how how the workers of Distrito Telefónica move around on a daily basis.

We analysed how much the London firefighters spend on saving animals’ lives by challenging our hypothesis against a null one. The larger and more available open data is to public services, the better we can analyse patterns and models to calculate how to save costs that have an impact on citizens and everything around them.

With predictive analysis tools created through biciMAD, we were able to analyse the most common patterns of cyclist accidents in the city of Madrid. And with the data obtained, such as the location of the accidents, we are able to get insights to better understand the characteristics and reasons for them and make better decisions.

Telefónica NEXT used mobile data to analyse patterns of movement of people in Germany which offered valuable information to plan transport in different areas and regions. The information acquired through the data benefits urban public transport institutions so they can develop new mobility plans.

With mobile and weather data, we have the capacity to analyse the impact of the storm that hit the San Jorge Gulf of Argentina in 2017.

Carto worked with the LUCA Transit platform to analyse mobility and transport data to minimize the impact of the closing of line 5 on the Madrid underground.

We used live mobility data and Smart Steps technology to design a different map of the Spanish regions as an alternative to the administrative one based on the flows of mobility of the people.

We used data and machine learning to characterize, analyse and predict the videogame League of Legends, one of the most popular eSport videogames of all time.

Working in close collaboration with the Movistar Sports Science team, we analysed datasets created by the Movistar Team during its competitions to see how Big Data can make a difference in their performance.

We used our Smart Steps technology to understand the profile and origin of the people who go to the Puerta del Sol to celebrate New Year’s Eve.

We analysed open datasets on refugees from the last few years to understand how the crisis has evolved over time.

We used our Smart Steps technology to identify the most popular destinations for people who leave Madrid during the first long weekend in December and how this varies year after year.

We conducted an in-depth analysis of Telefónica Global Solutions to reveal the insights behind international call traffic to better understand the effects of important events on communication patterns.

We combined Smart Steps data with Open Data to research Madrid’s pollution problem.

We observed Smart Steps data during rush hour in Madrid to see how Madrid’s workers get around and evaluate where there are more opportunities for car sharing and the use of public transport.

We analysed the US elections in real time with Philips Hue Lamps and Kibana in addition to using Sinfonier, one of the ElevenPaths products.

We used Big Data from IoT sensors during Hugo Scagnetti’s journey around the world on a motorbike to create a visualization to enable safer driving analytics.