Science of Big Data

« If we want to learn about the data, we must understand it. »

Today we had a conference dealing with our ability to interpret datas and information we receive every single day. It made us think about relationship with the fake (or not) news. About how data could be used ?

So first we took into acount the example of the taxi trips. In the US, specficially in New York here. Datas are useful in this field as much as for taxi companies, taxi drivers and taxi users. This can be useful on an economic plan as well as on a practical plan for example. People can know with data how much time will they take to go from an A point to a B point, so you can learn about traffic. Companies can see hot spots where people are demanding trips.

Then with datas, we can also notice the overcome of ridehailing apps on the yellow taxis. The audience of people using these apps has increased very fast during pas years. Datas can create graphs which could be useful for research or to compare statistics (e.g. passenger counts). We can observe that Nightlife and weather are also related to taxi trips with this information.


Big Data are defined by 3 features :

  • Volume.
  • Variety.
  • Velocity.

Big data, and large datasets in general, require specific skills to be used and understood:

  • Computer science.
  • Statistics.
  • Artificial intelligence.
In parallel, the huge amount of data has stimulated the development of entirely new research fields.

Outside science, the availability of large quantity of (free) data has created countless novel economic opportunities.

In turn, this has stimulated a lot of new jobs with specific competences.

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