Data lakes and data warehouses are essential components of modern data management strategies. A data lake is a centralized repository that allows organizations to store vast amounts of unstructured, semi-structured, and structured data in its raw format. This flexibility enables data scientists and engineers to perform various types of analytics and machine learning. In contrast, a data warehouse is a more structured environment designed for storing processed data, typically organized into tables and columns. It is primarily used for business intelligence and reporting, making it easier for analysts to derive insights from historical data. Both systems serve distinct purposes and are often used together to optimize data utilization.