Geotechnical Engineering is classified by many mining companies as the highest corporate, investor and operational risk associated with the development and successful exploitation of a mineral resource. Given the shift in culture towards geotechnical engineering and the influx of new exploration projects, the quantity and complexity of geotechnical data is increasing at exponential rates. Unfortunately, in some cases, data management techniques have lagged behind data capture processes, resulting in relatively primitive technologies to store highly sensitive and costly data. Under these primitive systems, there is no quantifiable handling on the quantity or quality of geotechnical data. The rollover effects of poor data management standards are significant and in severe cases, areas require redrilling or revaluation to capture lost data. The aim of this project was to capture, extract and upload geotechnical data into an easily accessible, single source geotechnical database. Using Rio Tinto Coal Australia (RTCA) as a case study, the project formed a framework for future database implementations by outlining the systematic project progression from data extraction to population and application of the database. By providing a single source database, frequent engineering tasks at RTCA were automated which significantly increased engineering efficiency and accuracy. Additionally, comprehensive Quality Assurance and Quality Control (QAQC) checks improved overall data integrity, resulting in enhanced data confidence.