Parquet, a data storage format, organizes data into columns and utilizes row groups and column chunks for efficient data processing. Its hybrid data organization format improves performance compared to traditional row-based formats. Metadata in Parquet files provides information about data structure, row groups, and column chunks, enabling efficient data access. The writing process involves collecting metadata, calculating row groups, and compressing column chunks to optimize performance and storage. Reading Parquet files leverages metadata to identify and decode specific data elements, maximizing performance for analytics workloads.