Analyzing and development professional competencies using graph models

Dinara Kaibassova (), Praveen () and Denis Odnourov ()

International Journal of Innovative Research and Scientific Studies, 2025, vol. 8, issue 9, 205-221

Abstract: This research explores the application of graph models and visualization tools for analyzing professional competencies with Kazakhstan labor market, provided by the National Chamber of Entrepreneurs “Atameken”(NCE). Using professional standards parsed from the National Chamber of Entrepreneurs “Atameken” documents, a comprehensive graph model was developed to represent the relationships between job positions, skills, knowledge, and qualification levels to better understand career pathways. Visualization and analysis of the graph models, constructed according to the professional standards provided by the National Chamber of Entrepreneurs, revealed several key insights into the structure of professional competencies. The model was implement using the graph database for querying and traversing the information . One major finding was the dependence of skills and knowledge on the Skills Qualification Framework levels, where foundational competencies were observed to span multiple qualification levels, while advanced, specialized competencies were concentrated at higher levels. This distribution emphasizes the layered nature of professional growth, with foundational skills acting as prerequisites for advanced roles. Furthermore, the graph analysis highlighted overlaps in skills and knowledge across related professions. Overall, the graph model successfully captures the layers and overlapped nature of professional growth as required and defined by the NCE standards. In Addition, the results demonstrate the utility of graph-based models for analyzing and visualising professional standards, offering a robust framework.

Keywords: Data analysis; Data structure; Graph databases; Graph models; Neo4j; Professional competencies; Qualification levels. (search for similar items in EconPapers)
Date: 2025
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