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Big Data 31 Aug 2016

Deconstructing a data analyst

The data generated by the endless amount of operations we engage in every day: transactions, medical inquiries, online publications… have paved the way for the ascent of the data analyst profile. A professional whose work is shrouded in myth and mystery.

So, what is it that data analysts do? What type of training do they need? What skills are linked to their job? We talked to two Big Data experts to learn a bit more about the profile of one of the hottest jobs today, behind data acquisition, analysis and visualization development.

1. Much more than just excel and SQL

Julia Díaz, head of innovation of Health and Energy Predictive of the IIC, recognizes that it is a profile where there is a huge range of variety. The Excel and SQL skills that requested in many job openings only cover the basic skills that many companies are looking for. In her opinion, boiling down the profile to such a point is very similar to what happened when “when computer age arrived and people thought that anyone who owned a computer was a programmer.” That is why opening should be also looking for other skills and expertise. Big Data is not everything that is analyzed using an excel spreadsheet, and an analyst is not someone who knows how to plot graphs using it”, he explained.

2. Specialization

In fact, depending on the field of activity, even the company, the set of skills and knowledge in-demand can hugely vary. The IIC of the Autonomous University (Universidad Autónoma de Madrid), for example, has defined different levels. “We have data scientists, data analysts and also what are known around the globe as citizen data scientists, people that analyze information at more basic levels,” said Díaz.

In any case, most of the people working for the institution have mathematical and computing backgrounds. These are people capable of carrying out an implementation, but who also have the mathematical knowledge to analyze, infer and arrive at conclusions… “Mastering Excel and SQL is not enough. What is important here is the value that the individual brings,” adds Díaz.

For Miren Gutiérrez, head of Deusto University’s ‘Data Analysis, Research and Communication’ Expert Program, Big Data’s value chain is extremely long and each one of its stages offers ample room for a possible specialization. “It is possible to master several skills, but, ultimately, when the scope and breadth of the project is rather large, it can only be tackled through a collective approach, where every individual puts their skills and experience at the service of the others.”

3. A task that requires teamwork

The analyst, therefore, must be capable of working as part of a team. At Deusto University this field of work is tackled from three perspectives: data for companies, data tools for engineers and data communication.  The three fields of activity have areas that overlap. “Thus, in the three areas everyone needs to master basic concepts in order to be able to extract, clean, analyze and visualize data. But that’s where the similarities end,” explains Gutiérrez.

In her program, for example, she focuses on how to find “stories" in the data and how to communicate them effectively, regardless of whether you are a public servant that needs to communicate public figures to the general public, a data journalist or a campaign leader in an NGO. What’s ultimately interesting is joining the different spheres to render more valid data analyses.

4. Analysts with a humanities background? Of course

Regarding these highly varied spheres, Deusto University’s expert recognizes that several of the people that she admires the most in the world of data analysis have a humanities background. “People who have been able to find the meaning, the narrative behind the data, and who have acquired the skills required to analyze and visualize them.”

Duncan Clark, from Kiln, is the living image of this characteristic. And this comes to prove that the best data analysts are not always computing scientists, mathematicians or statisticians.

5. Social usefulness

One of the things that Miren misses the most is that, many times, the analysis lacks the “for what” component. In other words, analysts are great with data, but their work often lacks social usefulness, a purpose. That’s where, probably, profiles more focused on sociology, journalism or biology become more relevant.

Robert Lynd already said it in 1939: knowledge always have to pursue an explicit ‘for what’. Without that, visualizations are worthless,” explains the expert.

6. Connection with the social context

Another interesting point when analyzing the profile of the analyst is that every database has been generated within a social, technological, economic and scientific framework, and can contain, and “frequently contains, errors and gaps.”

And this is something that, according to Miren Gutiérrez, should also be explicitly stated. “Let’s say that, if we do not it, we will be collaborating in a ‘for what’ for third parties and in a not very transparent manner. That's why I also think that the alleged scientific objectivity does not exist. It is the method that is objective. That is why we need to explicitly state, not just how the data were generated, but the purpose that any analysis seeks to fulfill.”

7. A set of skills

According to Gutiérrez, besides mastering technology, the data analyst must “be very inquisitive; have great analytical skills both to see both the big picture and the specific case that their work is addressing; the analyst has to be able to think in an innovative manner; has to have a knack for working as part of a team and sharing; and an eagerness to play, learn and marvel at things.”

8. Mobilizing and empowering civil society

The analyst works for society. In fact, it is just amazing to see how data can mobilize and empower people. “Initiatives such as the Ushahidi project for critical situations, natural disasters, and humanitarian emergencies are truly amazing,” explains Deusto University’s expert.

“The projects using this platform help generate a process that ultimately leads “victims” to take control over their situation and help others. I think that this type of social usefulness of the data analysis and visualization techniques should make people feel passionate about them,” she concludes.

Educate yourself to become the best

Today in Spain, there are many professionals educating themselves and striving to improve on a daily basis. In fact, many of them are achieving major accomplishments. Álvaro Barbero, for example, came in second in the TEXATA 2015 contest, or the Autonomous Community’s own IIC, which has also been awarded by the Big Data Foundation.

“Many companies both from our country and the rest of the world entered the contest. We’re very proud of Barbero, who not only finished second in the world, but was also the only shortlisted candidate from Spain,” concludes Julia Díaz.

Today, several training programs, both in Spain and international, offer analyst training programs in different modalities. Each one follows its own approach. “There are also abundant courses, tutorials and open programs online for those willing to explore and learn by themselves.”

One of her favorites is Coursera (a massive open online course), which offers guidance for people who have already attained a certain level of knowledge and want to develop specific skills, such as network theory and analysis. This is how Miren Gutiérrez opens the door to anyone wishing to venture into the world of data analysis. An enthralling task, laden with nuances and a work in progress.