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Big Data

Big Data analyzes a large volume of data to obtain information, gain knowledge and generate value.

What Is It?

Big Data is a term that describes a large volume of data in terms of its size (volume), complexity (variability) and velocity of growth. When analyzed, these data can be transformed into information, which can then be used to build corporate knowledge and, therefore, add value to companies that know how to make use of this information. When applied, they form part of a company’s know how.

Big Data Applications

When variables are measured correctly and prior sensorization is optimal, any process can be analyzed and generate large amounts of data: from hydraulic valve performance to bag movement through an airport, and from vehicle traffic in Managed Lanes to a company’s decision-making boards.


Managed Lanes are toll roads whose pricing depends on traffic intensity and other variables derived from on Big Data, such as the estimated demand during certain times of the day based on historical data. These models play an important role when it comes to using infrastructure more efficiently and minimizing pollutants such as CO2.

In addition, we are working to create open data systems with administrations. These systems encourage the use of massive data and artificial intelligence to bring innovation to private companies like Zity, which are able to integrate their systems and generate new business models.


Something similar is happening in our cities, where the first phase of sensorization has achieved continuous measuring of pollution, facilitated the creation of years of noise maps, and allowed traffic to be analyzed in dozens of key spots. In some cities, such as New York, the amount of data being collected is massive.

All of this will help generate better decarbonization policies that improve city air quality, create priority policies to minimize noise pollution caused by mobility, and manage traffic to reduce jams in urban areas. Big Data is a key tool for the 4.0 economy and smart cities.

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