Data-driven decision-making options for less tech-savvy users

This study explores the application of data-driven decision-making tools for users with limited technical expertise, focusing on the usability and effectiveness of Power BI and Oracle Analytics in real estate investment scenarios. A custom dataset of real estate transactions in Žilina, Slovakia, was collected and preprocessed to evaluate how these platforms enable non-programmers to perform data transformation, analysis and predictive modeling. Both tools were assessed on their ability to handle common data processing tasks, train predictive models, and generate actionable insights. Results show that while Power BI is more intuitive for data preprocessing, Oracle Analytics excels in model training and prediction. Combining the strengths of both platforms could provide a comprehensive solution for users with limited technical skills. This research offers practical recommendations for selecting and using these analytics tools in real-world decision-making contexts, particularly in the domain of real estate investment.