The master's thesis explores the use of data mining techniques to determine the digital maturity level of small and medium-sized enterprises (SMEs) in the Ternopil region. The research focuses on clustering analysis to identify patterns and characteristics of SMEs based on their digital maturity. The study analyzes survey data collected from entrepreneurs in the Ternopil region to assess the current state of digital transformation in their businesses. The research aims to develop a data analysis approach that can help SMEs improve their digital capabilities and adapt to the changing business environment. The thesis also discusses the importance of digital transformation in SMEs, the challenges they face in adopting digital technologies, and the role of data analysis in supporting business decision-making. The study proposes a method for clustering SMEs based on their digital maturity level, using various data mining techniques and metrics. The results of the analysis provide insights into the digital maturity of SMEs in the Ternopil region and highlight the need for targeted support and resources to help them improve their digital capabilities. The research contributes to the understanding of digital transformation in SMEs and provides practical recommendations for enhancing their digital maturity. The thesis is structured into several sections, including an introduction, literature review, methodology, results, and conclusions. The study uses a combination of data analysis techniques, clustering algorithms, and statistical methods to analyze the data and draw meaningful conclusions. The research is supported by a comprehensive literature review and is based on real-world data collected from SMEs in the Ternopil region. The findings of the study have practical implications for policymakers, business leaders, and researchers interested in digital transformation and data analysis in SMEs. The thesis is written in Ukrainian and includes a detailed analysis of the data, the methodology used, and the results obtained. The study is an important contribution to the field of data analysis and digital transformation in SMEs, providing valuable insights and recommendations for improving the digital maturity of small and medium-sized enterprises.The master's thesis explores the use of data mining techniques to determine the digital maturity level of small and medium-sized enterprises (SMEs) in the Ternopil region. The research focuses on clustering analysis to identify patterns and characteristics of SMEs based on their digital maturity. The study analyzes survey data collected from entrepreneurs in the Ternopil region to assess the current state of digital transformation in their businesses. The research aims to develop a data analysis approach that can help SMEs improve their digital capabilities and adapt to the changing business environment. The thesis also discusses the importance of digital transformation in SMEs, the challenges they face in adopting digital technologies, and the role of data analysis in supporting business decision-making. The study proposes a method for clustering SMEs based on their digital maturity level, using various data mining techniques and metrics. The results of the analysis provide insights into the digital maturity of SMEs in the Ternopil region and highlight the need for targeted support and resources to help them improve their digital capabilities. The research contributes to the understanding of digital transformation in SMEs and provides practical recommendations for enhancing their digital maturity. The thesis is structured into several sections, including an introduction, literature review, methodology, results, and conclusions. The study uses a combination of data analysis techniques, clustering algorithms, and statistical methods to analyze the data and draw meaningful conclusions. The research is supported by a comprehensive literature review and is based on real-world data collected from SMEs in the Ternopil region. The findings of the study have practical implications for policymakers, business leaders, and researchers interested in digital transformation and data analysis in SMEs. The thesis is written in Ukrainian and includes a detailed analysis of the data, the methodology used, and the results obtained. The study is an important contribution to the field of data analysis and digital transformation in SMEs, providing valuable insights and recommendations for improving the digital maturity of small and medium-sized enterprises.