The best features of Azure Databricks I use the most include schema evolution, auto merge, and efficient handling of shuffles or transformations, along with Z-ordering and partitioning, which enhance the performance of data transformation. Additionally, Delta format, time traveling, versioning, and ACID properties are sophisticated features that provide great support for cloud Lakehouse architecture. Azure Databricks has positively impacted my organization by allowing us to build medallion architecture or Kappa architecture for handling both scheduled and streaming data, and after establishing the ingestion framework, the existing data services handle transformations and cleansing effectively, which means we rarely need to change services. I also make use of Unity Catalog, RBAC, ACL, and Purview for data governance and security, enabling efficient management of scalable solutions across the organization.
