Careers in big data

The science of big data has recently become one of the main pillars of modern society, based on digitalisation.

In an environment where the flow of data we generate every day is increasing, someone has to take care of collecting it, storing it, protecting it and most importantly of all: knowing how to use it.

This is when the professional big data specialist comes into play, a profile that is studied in more depth in, and that you can get the skills for, with the Master in Big Data Analytics at Universidad Europea.

The big data specialist is one of the most in-demand profiles nowadays, as all companies, regardless of the sector they belong to, require a professional capable of transforming all this data into valuable information for their business.

What does it take to work in big data?

Whether you are thinking of starting from scratch (here we explain more about what big data is) or broadening your knowledge, to work in big data you will need specific, up-to-date training adapted to the reality of the sector.

Some of the skills you will need to know or enhance to open the doors to this sector are the following:

Programming languages: SQL and Python

Used today by most companies that work with data, the importance of SQL (Structured Query Language) lies in its ability to function in a simple and practical way in the management and downloading of information. Another of the most popular languages due to its ease of use and versatility is what we know as Python.

Machine Learning and artificial intelligence

Machine Learning is a subcategory of Artificial Intelligence that allows a machine to process large amounts of data based on its experience with past data.

Today, the combination of Machine Learning and big data is essential to the success of many companies thanks to the ability of these two elements to collect, store and manage large amounts of data in the most efficient way.

Data mining: management, planning and quantitative analysis

Big Data professionals must be able to differentiate the truly valuable data from the rest (Data Mining), as well as to identify possible patterns and trends in their analysis. To do this, they will need extensive management and analytical skills and must adhere to prior planning.

Data visualisation

The enormous amount of data with which this discipline works requires Big Data specialists to have the ability to generate interactive graphs and maps that help them to better assimilate all the information.

Capacity for constant learning

The data handled in Big Data grows and transforms every day, so it is important for the person interested in working in this field to be able to adapt to different situations and to be constantly trained in the latest developments in the sector.

Career opportunities in big data

Big data specialists are among the most sought-after profiles by companies in many sectors. Among the most popular professions, we can find three:

• Data analysts: this is the most sought-after big data career path at present, thanks to its versatility to work in a large number of sectors. Data analysts are in charge of processing and performing statistical analysis of the data handled by the company. Their tasks include producing reports or designing and locating key indicators to achieve business objectives. If you are interested in this profession, have a look at this article about how to become a chief data officer.
• Data architects: have you been wondering ‘what is a big data archiect?’ Well; they are in charge of designing and implementing a software platform that is capable of supporting the large volumes created by big data. In addition, it is advisable for these professionals to have notions of cybersecurity, as another of their functions is to guarantee the security of the stored data.
• Data scientists: one of the most popular and important professionals due to the tasks they perform. Data scientists are responsible for visualising data and configuring learning models based on the data extracted by engineers. To do their job, they need to be proficient in programming languages, statistics, mathematics and machine learning.