Integrating Python Into Power BI for Analyzing and Predicting Digital Development: Case Study – Balkan Countries

Abstract

The modern era with emerging technologies leads to the generation of an abundance of data, in the correct interpretation of which visualization plays a key role. The accelerated growth of the volume and complexity of data emphasizes the need for advanced ways of their transformation, visualization and analysis. By applying quantitative, empirical and qualitative methods, this scientific paper investigates the time required to perform complex data transformations in the Power BI visualization tool, in the case when they are provided manually and by applying Python code, i.e. integrating a Python script, and analyzes the efficiency and practicality in both cases through a specific example of analysis and prediction of the digital development of selected Balkan countries. The research is based on processing secondary data on the determinants of digital progress taken from official sources, empirical research and observation of IT and BI professionals for whom the time of performing assigned tasks was measured and subjective assessment of personal perceptions through an interview. All results pointed to the fact that the use of Python scripts within Power BI significantly reduces the required work time and increases efficiency while improving the accuracy, user experience and practicality of this tool, which is an important step towards adopting new advanced practices in visual data analysis.