We live in an age where data is plentiful. Let’s think for a moment: what data of ours can be found on the Internet floating in cyberspace? First name, last name, maybe address (product of some purchase we made online and that of course came home), the songs we listen to (from our Spotify or Soundcloud lists), the articles we research (product from the pages we see on Amazon and in other online stores), among others.
This amount of data, once processed and analyzed, can lead us to certain conclusions both about individual people and about the set of populations, including to differentiate them according to their preferences and which, in turn, can be applied to specific individuals in the form of recommendations. For this, the Big Data discipline was created .
We can define Big Data as a computer science discipline that deals with capturing, managing and analyzing large data sets, drawing conclusions, as well as applying these conclusions to more specific cases.
That is, Big Data is a complete discipline, not just collecting and storing large data sets.
At a time when data is not only scarce, but where we often have more than we would like or could be really useful, Big Data is also about choosing the data that is really useful to do. analysis and drawing of conclusions.
The ultimate goal of Big Data is to gain a benefit to our company or initiative.
Let’s look at a concrete case: suppose we have an online music store and from what our customers listen to, we keep certain information, such as the song title, artist name and the times it is played.
Once all these data are analyzed, we can reach several conclusions. It can be said that each of our clients is used to classifying their musical options into one or a few specific genres, and that we can classify each of the groups and artists we have in our catalog within these genres.
Then, we can use Big Data to recommend our store customers to listen (and buy of course!) music from certain groups that suit their preferences.
In this way, we offer a service that is more tailored to the personal preferences of each of our customers, making it more personalized and, therefore, offering “your store” instead of a generic store.
Big Data is the discipline used, for example, in social networks to suggest pages and profiles to follow, or even content sites to suggest readings.
Amazon is one of the companies that exemplifies the use of Big Data, as from the analysis of queries and purchases of all users, it is concluded that suggestions for new products must be shown to each individual user.
However, it should be noted that not everything that is suggested to us on the Internet is the result of the analysis of trends through Big Data.
The commercial agreements between the companies that make the suggestions and the manufacturers of the products must also be taken into account.
Technologically, the use of Big Data solutions needs a lot of processing power
That’s why they are used to using dedicated computer systems, such as large servers and dedicated facilities that specialized companies rent for more concrete studies or for customers who use them all year round.
Big Data often requires dealing with collections of data that are not fully structured. That’s why specific solutions are needed for its use in this type of application.
They say that technical profiles specialized in Big Data will be in high demand in the future
In other words, if you’re thinking of finding a job in computer science, you should seriously think about specializing in the big data field, as there’s a lack of supply to cover the demand.
Data collection for further analysis is not only carried out on the Internet and about people, but can be done using IoT sensors.
In this way, for example, we can analyze the behavior patterns of drivers, collecting data from parking sensors in order to know the peak hours or movement patterns.