Data lakes and data warehouses are essential components of modern data management strategies. While both serve as repositories for storing large volumes of data, they cater to different needs and types of data. A data lake is designed to store unstructured, semi-structured, and structured data in its raw form, allowing for flexible analytics and exploration. In contrast, a data warehouse is a more structured environment that stores processed data, typically organized into tables for easy querying and reporting. Understanding the differences between these two systems is crucial for organizations aiming to leverage data effectively for decision-making and insights.