Building a Python-Based Data Lake

Data lakes are vital for modern data ecosystems, allowing organizations to store and analyze large volumes of varied data without requiring a predefined schema. This guide details setting up a Python-based data lake using MinIO, PyIceberg, PyArrow, and Postgres, ideal for small to medium setups due to its simplicity. The step-by-step instructions cover installation of libraries, configuring SQL catalogs, data transformation using Pandas and PyArrow, and querying data. Advanced operations using DuckDB are also explored, showcasing robust data handling with flexibility and scalability.