Abstract Today's buildings are not only energy intensive, but also information intensive. Massive amounts of operational data are available for knowledge discovery. Data mining (DM) has excellent ability in extracting insights from massive data. This paper performs a case study on the assessment of building operational performance using DM techniques. Typical DM techniques are compared and considerations for choosing specific DM techniques for the case study are presented. The methodology developed has been applied to analyze the data retrieved from a university building in Hong Kong. Useful insights have been obtained to identify typical operation patterns and energy conservation opportunities.