Data lakes hold a significant place in big data applications as they provide a centralized repository for storing vast amounts of structured and unstructured data. Unlike traditional databases, data lakes allow for the storage of raw data without prior organization, enabling organizations to analyze diverse data types. This flexibility supports advanced analytics, machine learning, and exploratory data analysis, facilitating insights that drive better decision-making. Additionally, data lakes can scale easily, making them suitable for organizations with increasing data needs, while also fostering collaboration across various data science disciplines.