Concept in Definition ABC

We live in an age where data abounds. Let's think about it a bit: what data about us can there be in Internet, floating in cyberspace? Name, surname, perhaps address (product of a purchase that we have made online and that, naturally, has had to arrive at our house), music what we hear (from our Spotify lists or what we listen to on Soundcloud), what articles we look at (product of the pages we see on Amazon and other online stores), and many more.

This amount of data, once processed and analyzed, can lead us to conclusions, both about individual people and about sets of population, and even to differentiate these according to their preferences, conclusions that, in turn, we can apply to specific individuals in the form of recommendations. For this, the discipline of Big data.

We define the Big data as the discipline of computational science that deals with the capture, management and analysis of large data sets, drawing conclusions from this analysis, and applying these conclusions to cases concrete.

That is, the Big data It is a complete discipline, and not just the collection and storage of large data sets.

In an era in which data is not only not scarce, but in many cases we have more than we would like or that can be really useful, the Big data it also deals with how to choose the data that is really useful to us for conducting analyzes and drawing conclusions.

The ultimate goal of Big data is to obtain a benefit for our company or initiative.

Let's take a concrete case: let's suppose that we have an online music store and that, from what our customers hear, We store information such as the song title, artist name and the number of times each is played. song.

Once all these data have been analyzed, we can reach several conclusions. Let's say we see that each of our client It is customary to classify their musical options in one or a few specific genres, and that we can classify each of the groups and artists that we have in our catalog in these genres.

So, we can use the Big data to recommend our store customers to listen to (and later buy, of course!) music from certain groups that suit their preferences.

In this way, we offer a service more adjusted to the personal preferences of each of our customers, making it more personalized and, therefore, giving them “your store” instead of a store generic.

The Big data It is the discipline they use, for example, in social networks to suggest pages and profiles to follow, or content websites to suggest readings.

Amazon is one of the businesses that exemplifies the use of Big dataSince from the analysis of the inquiries and purchases of all the users of this famous website, it is concluded which suggestions for new products should 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 trend analysis through Big data.

We must also take into account commercial agreements between the companies that make the suggestions, and the manufacturers of products so that theirs are the ones that appear in said suggestions.

Technologically, the use of solutions Big data requires great processing power.

That is why they get used to using dedicated computer systems, such as large servers, and facilities dedicated firms that specialized firms rent for specific studies or to clients for use throughout the entire year.

Many times the Big data it requires dealing with data collections that are not fully structured. That is why specific solutions are required for use in these types of applications.

It has been said that technical profiles specialized in Big data they will be in high demand in the future.

In other words, if you are thinking about having a job in the field of computer science, you should think seriously specialize in the area of Big data, in which there is a lack of supply to cover demand.

The collection of data for subsequent analysis is not only carried out on the Internet and on people, but can also be done using IoT sensors.

In this way, for example, we can analyze the behavior patterns of the drivers, collecting data from the parking sensors to know the busiest hours or the driving patterns. movement.

Photos: Fotolia - lasse / georgejmclittle

Topics in Big Data