The primary use of data lakes in big data analytics is to store vast amounts of structured and unstructured data in its raw form. Data lakes provide a centralized repository that can accommodate various data types, including text, images, and logs, allowing organizations to analyze diverse datasets without the constraints of traditional databases. This flexibility supports advanced analytics techniques, such as machine learning and real-time processing, ultimately leading to better data-driven decision-making. Moreover, data lakes help businesses harness the value of big data by enabling scalability and accessibility.