Data lakehouse

Challenged by the newer demands to derive value from the vast and ever-increasing unstructured data, it became important to come up with a new arrangement that does not try to force unstructured data into the strict models of a data warehouse. The data lakehouse blurs the lines between data lakes and data warehouses by enabling the atomicity, consistency, isolation, and durability (ACID) properties on the data in the data lake and enabling multiple processes to concurrently read and write data.

With this, transformed data in open formats such as Apache Parquet can be consumed for feature engineering and machine learning (ML) workloads and can also be used for analytics.