This article presents a method to create a digital twin for sauna. The digital twin deploys a data analytics method based on fuzzy similarity measure for data summarization to provide real-time actionable instructions. The intended outcome of the digital twin is enhanced safety and improved sauna experience. In this research, we collected the data through experimentation with a testbed and interviews. Our implemented digital twin simplifies the readings of nineteen sensors into a single graphical form for the user that illustrates the overall sauna conditions and assists the sauna manager with condition optimization. Results illustrated the effectiveness of the digital twin in achieving an enhanced sauna condition for the users and providing the sauna manager with a decision support system. The method of creating the digital twin described in this article has potential implications for the condition monitoring, predictive maintenance, and enhancing the safety and security of complex systems.