Indoor radon represents a known hazard to public health, namely, its relationship with lung cancer. The adoption of data analytics tools for indoor radon human exposure risk assessment is crucial for building management decision-making and is a fundamental requirement for the implementation of remediation measures. This work presents the implementation of a data warehouse and an OLAP cube as components of a more comprehensive IoT-based system, which has been developed for continuous indoor radon gas management in public buildings. The proposed data warehouse consists of a three-tier data storage structure to store historical measurements. Although the adopted approach has been tested with a small number of IoT sensors, the operation of the data warehouse and OLAP server assures that the system is viable and highly scalable. The increase in the number of active IoT sensors deployed in new buildings, cities, and districts will increase the richness of the data, which will help to foster even better models.