This module introduces Delta Live Tables (DLT) in Databricks and its role in simplifying ETL workflows. You will start by understanding the limitations of procedural ETL, such as manual coding and debugging challenges, and explore the benefits of a declarative approach. The module covers Datasets and Views in DLT, explaining how Datasets define and store transformed data, while Views act as logical layers for intermediate transformations and quality checks. You will also learn about Data Quality Expectations, which enforce validation rules at every stage.
Finally, you will build and run DLT pipelines using Python and SQL, defining datasets, managing dependencies, scheduling workflows, and monitoring execution for efficient data processing.