Data scarcity refers to the lack of sufficient data to make informed decisions or conduct thorough analyses. This situation can arise in various fields, such as machine learning, where algorithms require large datasets to learn effectively. When data is limited, it can lead to inaccurate models and unreliable predictions. In many cases, data scarcity is a result of privacy concerns, resource limitations, or the inherent difficulty of collecting certain types of information. For instance, in healthcare, obtaining comprehensive patient data can be challenging due to regulations. Addressing data scarcity often involves innovative data collection methods or leveraging existing datasets more effectively.