Occupancy-based pattern mining has emerged as a significant research topic in recent times. This paper presents a comprehensive survey on occupancy, which serves as a measure to augment the significance of patterns. The survey covers various types of patterns, including frequent itemsets, high utility itemsets, frequent sequences, and high utility sequences, all in the context of occupancy. Additionally, the paper delves into techniques aimed at reducing the search space in the aforementioned pattern mining problems. These techniques are crucial for improving the efficiency and scalability of the mining process, especially when dealing with large-scale datasets. Furthermore, the paper discusses potential research extensions for occupancy-based pattern mining. These extensions could explore new applications, explore novel algorithms, or further enhance the effectiveness of occupancy as a measure for pattern evaluation. In general, this survey provides an important resource for researchers interested in understanding and advancing occupancy-based pattern mining techniques.