Data Science is science about  methods of data analyzing and obtaining of important information and knowledge. It uses methods and theories taken from many areas of mathematics, statistics, computer science. It is closely intertwined with such areas as Machine Learning, Cognitive Science, technology for working with Big Data.

In general, Data Science it is a set of specific disciplines from different areas that are responsible for data analysis and finding optimal solutions based on them. Previously, this was done only by mathematical statistics, then bu using  machine learning and artificial intelligence, which as methods of data analysis added to mathematical statistics optimization and computer science (informatics).

The responsibilities of specialists in this field include programming, mathematical models and statistics. In addition, it is important for professionals to understand what is happening in the subject area (for example, in financial processes, bioinformatics, banking or even in a computer game).

The benefits of data analysis can be obtained from all more or less applied areas where there is enough data. For example, speaking about medicine, algorithms allow better  to diagnose the disease and prescribe a treatment plan. Personnel management can be improved if algorithms help to detect in advance that communication problems have begun in the team.

Nowadays, thanks to Data Science, simple decisions can be automated when there are clear rules. For example, cybersecurity systems work almost entirely on machine learning algorithms, deciding whether to send an email as spam or block it as a questionable transaction. All this is done on the basis of existing data.

The next step of Data Science using is to automate more complex decisions or create a smart assistant. This is followed by the automation of task chains or even specific professions.

Guarantor - Doctor of Technical Sciences, Professor, Professor of the Information Systems and Networks Department , Berko Andriy Yulianovych