Abstract:

Recent decades have witnessed an increased growth in data generated by humans and machines, giving birth to the Big Data paradigm. Analyzing Big Data allows analysts, researchers, and business users to make better and faster decisions using data that was previously inaccessible or unusable. Moreover, Data Science has emerged as a new inter- and cross-disciplinary field, which includes statistics, informatics, computing, communication, management, and sociology. Data science focuses on analysis and uncovering hidden meaningful patterns, correlations, complex event processing and other insights.

This paper is related to Data Science and the Data Scientist’s skills. The dimensions and challenges of Big Data and Data Science fundamental concept are briefly described. As the ways of capturing, collecting, aggregating and analyzing large and heterogeneous datasets needs powerful technologies and specific skills from Data Science a new profession emerges – a Data Scientist. The Data Scientist has the task of making sense out of the vast data and helping the organization in informed decision-making. It is therefore essential that the Data Scientist has to possess a lot of skills to face the serious data, process and management challenges. This study aims to discuss ethical concerns related to Big Data analytics which raises some topical issues about the Data Scientist’s skills to reflect on.

The paper’s primary focus is on some problems and constraints imposed to Big Data analytics according to the newly introduced GDPR (General Data Protection Regulation). Organisations need to ensure that their data processing activities are carried out in accordance with the Data Protection Principles set out in the GDPR. As they are expected to be extremely challenging exploring the Data Scientist’s ethical skills are timely to discuss. In this paper ethical skills are considered separately to emphasize the importance of meeting Data Protection requirements which will benefit both organisations and individuals in a Big Data context.

Keywords:

Data Science, Data Analytics, Big Data, GDPR.