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Regular version of the site
Educational Programme
Final Grade
Year of Graduation
Mariia Semina
Big Data in Human Resources
Business Informatics
(Bachelor’s programme)
Despite the sufficient amount of studies and papers on big data in human resources, this field is still under-researched and the discussion spins around the significance of big data in HR. The recent problem of human resource management is to understand what decisions people still should take and what can be put into the hands of technology.

The primary aim of the proposed study is to identify and analyze the specifics of big data use in human resource management.

Within this broad purpose the following goals are addressed:

• Consideration of the concepts of "big data" and "human resource management".

• Review and analysis of HR digitalization trends.

• Analysis of big data use in HR.

• Description of the approach that combines cultural profile of the employee and big data analysis.

• Consideration of the approach benefits and risks.

• Forecasting of factors that contribute to the development of the analytics environment in organizations.

The general research perspective is qualitative – it will primarily focus on secondary data gathered from existing researches. The first method that is going to be used is the secondary research. The second method is the case study research that helps to understand a complex issue and can extend existing experience or add depth to what is already known through previous researches.

In the course of the study, identifying the candidate's soft skills was determined as a main problem of recruitment. As an opportunity to improve the recruitment process, it is proposed to use cultural profiles compiled on the basis of Hofstede’s parameters. The next stage of the proposed approach is the use of big data analysis on hard skills and soft skills of the candidate. The paper also discusses the advantages and risks of this approach and factors that can facilitate the use of analytical tools and big data in organizations.

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