Data Formats and Compression in Data Engineering: Best Practices for CSV, Excel, JSON, Parquet, and Avro

Choosing the right file format and compression strategy is crucial in data engineering to optimize storage and data transfer speeds. Common data formats include CSV, Excel, JSON, Parquet, and Avro, each with their own pros and cons. Various compression types such as GZIP, BZIP2, Snappy, LZO, and built-in options for formats like Parquet are discussed, alongside their best use cases. The timing of compression—whether during or after data transformation—also significantly impacts efficiency and storage. Practical recommendations include assessing use cases, optimizing at multiple stages, and continuously testing and monitoring the performance impacts of different strategies.