| Abstract [eng] |
Relevance of the Topic. Organizations use big data in the recruitment process, as it is the recruitment process that is one of the essential processes of an organization to carry out its activities effectively. The recruitment process covers all activities and practices of organizations, which in turn helps to identify and attract potential candidates, optimizing the strategy of the recruitment process. Based on the analysis of big data, organizations can more effectively select the most suitable employees according to the relevant parameters, based on skills, specific knowledge, experience, personality. The analysis of big data can help not only to attract the right candidates, but also to determine how many employees will be needed in the future, it is to predict recruitment needs in real time. Also, not only is the collection and analysis of big data important to organizations, but also the sources of data extraction. Properly selected sources of big data allow organizations to accumulate high-quality, value-creating data that, in further analysis, contributes to a more objective decision-making, that is, a fully appropriate candidate selection (Scholz, 2017). Object of the Project – big data in recruitment. Aim of the Project - develop big data in recruitment process classifier. Tasks of the Project: 1. To reveal the concept of big data and determine the typology of big data, sources and their classification criteria; 2. Define the essential stages of the recruitment process; 3. To prepare a classifier of big data in recruitment process; 4. Empirically evaluate the classifier of big data in recruitment process. Key Research Results. The study revealed that in the I stage of the recruitment process, informants use structured, semi-structured and unstructured data types, these data are obtained from sources such as, internal databases, external databases, information portals, personal portals, social media, cloud computing, internet of things, business management systems. Unstructured data is extracted in particular from external databases, information/personal portals such as the career page and other job posting platforms, and social media to obtain additional information about candidates. Structured data is extracted from internal databases, business management systems as other informants store already structured data in the databases of their organizations and use the existing accumulated database of candidates. Semi-structured data is extracted from cloud computing, it accumulates, compares data, from the internet of things to support more efficient processes, to verify knowledge. The informants classify the types of big data according to the competencies, experience, required position and technical knowledge of the candidate. Informants classify big data sources according to the reliability of the extracted data, according to the level of position sought, and the flexibility of the sources. Unstructured data provides the most information to informants, the best results for informants are generated by internal databases, information portals, personal portals. In stage II of the recruitment process, informants use the same data types, extracting these data from the sources listed above, with the exception of the internet of things. Unstructured data is extracted precisely from external databases, to form and submit tasks, information/personal portals, and social media. Structured data is extracted from internal databases, because the preparation of tasks for candidates uses structured data in databases, structured information about candidates, from business management systems, it is used the accumulated database of candidates, for comparison and selection of candidates. Semi-structured data is extracted from cloud computing, which stores and processes the received information. The informants classify the types of big data according to their competencies, experience, required position, technical knowledge of the candidate and data format. Many informants do not classify big data sources in the II stage of the recruitment process, as the classification is already done in the I stage and emphasize that it is most important to classify big data types at this stage, other informants stated that they classify sources according to the position level. In the III stage of the recruitment process, the informants use the same types of data as in the other stages, extracting these data from the sources listed in the first stage, with the exception of the internet of things and personal portals. Unstructured data is extracted from external databases, information portals, social media, platforms such as Facebook and others. Structured data is extracted from internal databases, as they also use their own structured data when selecting/comparing candidates, as well as from business management systems, preparing a value proposal for the candidate, resolving salary issues. Semi-structured data is extracted from cloud computing, which compares the data collected about candidates with each other, and selection is performed. The informants classify the types of big data according to the competencies, experience, technical knowledge of the candidate and salary expectations. Informants do not classify major data sources in stage III of the recruitment process, as all available information is mainly assessed/compared at this stage. |
