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 advanced analytics and machine learning. In contrast, a data warehouse is a structured storage solution designed for analyzing processed data, typically organized into tables and columns. It supports business intelligence and reporting needs by providing ready-to-analyze data. Together, these technologies complement each other, catering to different user requirements and analytical purposes.