Delta Live Pipelines (DLT) simplify data engineering by automating infrastructure management, data quality checks, and monitoring while allowing developers to focus on transformation logic using SQL or Python. The framework supports both streaming and batch workloads through a declarative approach, handling common tasks like incremental data loading and SCD model creation. DLT pipelines can be created via code or Databricks UI, implementing medallion architecture patterns with built-in features for data lineage, quality reporting, and performance optimization.
Table of contents
Delta Live Pipelines Explained: Concepts to ImplementationCreating a Delta Live Table (DLT) Pipeline in DatabricksScenario: Customer Data Pipeline Using Delta Live TablesSort: