Data analysis can do a lot of good
To be clear, the scandalous revelations surrounding Cambridge Analytica are discrediting an exciting and important profession. Collecting data today is a necessary task that is indispensable to the modern economy.
And good things can happen to it too - just think of the traffic data analysis that allows us to regulate traffic flows much better. Or to help patients with health data much more targeted. Without data, it would not be possible to solve challenging problems.
The Sexiest Job of the 21st Century?
It is no coincidence that the job of data scientist was described by Harvard Business Review authors Thomas H. Davenport and DJ Patil as “The Sexiest Job of the 21st Century”. Nevertheless, one has to be aware that this job requires extensive knowledge in addition to a great responsibility in dealing with the data.
Because it is important that sensitive data is handled responsibly. Well-founded training helps here. For example, the former Director of Research at Cambridge Analytica and later whistleblower Christopher Wylie, the son of two physicists, had taught himself to program after dropping out of school and got his job at Cambridge Analytica without any formal qualifications.
What education and skills are needed?
I have studied computer science myself, but today my job is rather a mix of mathematician, computer scientist, statistician, software developer and business process development manager, coupled with a good dose of common sense.
But sure, my education has only laid the foundation. What challenges Company in terms of large amounts of data today and were years ago, this knowledge I have acquired in the course of my work.
Task of the Data Scientist
But what does an expert, who is located between big data, analytics and business intelligence, do in his daily work? And what skills should he bring with him? And what skills should the ideal data scientist in programmatic bring to soft as well as hard skills?
Data Science is an essential element for all stages of the programmatic process. Built on user data and user habits, the ecosystem of digital advertising is both a challenging and stimulating application for all data scientists who want to work on innovative and influential issues.
Like a forensic at CSI
Basically it is with my still young professional field to generate from the fast growing data mountains (Big Data) exactly the information, which the enterprise needs in order to work more efficiently. The goal is to use the existing data sets meaningfully rather than hoarding them into data stores.
My work and my customer interviews sometimes remind me of a forensic from the TV series CSI. This is caused by the analysis and combination of the smallest evidence. In companies it is mainly about intelligently combining the data to show improvement potentials as well as to a certain extent reliably in the future.
Intelligently linking data
Predictions do not come from the gut, but are based on the latest findings and methods of Predictive Analysis.
One of my declared goals is to provide not only the know-how, but also the right tools to carry out this profession professionally and to make my work easier. It also benefits other companies by showing them how to intelligently link their data to existing tools, such as enterprise search solutions. With the result, in search queries a comprehensive overall view on the queried topics to get.
Trainings to the Data Scientist
I still remember the days when I watched my brother transfer data with a pair of acoustic couplers, or I even tried to access the Internet a few years later with my 28,8K modem and finally with a sensational 56k modem - unthinkable today.
Today only a few training possibilities exist such as a course at the Fraunhofer Institute. A good basis is training in computer science, statistics, business informatics or mathematics and a high degree of social competence. In this profession, it is important to think in a cross-departmental manner in order to correctly link the requirements of the individual departments and to identify from the overall picture exactly those points which are to be further developed to the benefit of the company.
Why is a data scientist so important?
Of course, I also had a personal motivation to take up this job: I found “fascinating” not only Mr. Spock and the spaceship Enterprise when I was young, but also mathematics and, of course, computers.
However, the job today has little to do with child games: A data scientist must identify with 100 percent with the company, because he also bears a great responsibility with regard to the sustainable and responsible handling of the data. Regardless of size or industry, data volumes are constantly increasing and it is becoming increasingly difficult to maintain an overview and leverage insights to the benefit of the business. That's why the data scientist is so important.
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