This thesis examines the pivotal role of quantitative data in rural development decision- making, emphasizing the identification and application of critical data attributes for rural area development. Through a Design Science Research (DSR) methodology, this study constructs and validates a list of attributes focused on demographic, economic, infrastructural, connectivity, and environmental metrics crucial for rural areas. The research highlights the substantial risks of pseudo-development due to data gaps and inaccuracies and stresses the importance of precise, reliable data for effective planning and implementation. The findings advocate for advanced data collection methods and tailored data-driven approaches to address the attributes found to be important for rural areas and the unique challenges rural communities face. The thesis suggests a list of attributes that adhere to these unique use cases.