Data Storage Approaches

Common approaches include using ETL pipelines and integration tools to convert and unify data in formats like CSV, JSON, and XML. Through these tools, data engineers can load and transform the data, saving it in a common format for later use.

Challenges related to data storage are addressed by optimizing internal structures (e.g., using Parquet for large volumes), applying indexing strategies, and storing data in scalable environments such as cloud warehouses.