Documentation | Release Notes | Examples

DLT-META is a metadata-driven framework based on Databricks Delta Live Tables (aka DLT) which lets you automate your bronze and silver data pipelines.

With this framework you need to record the source and target metadata in an onboarding json file which acts as the data flow specification aka Dataflowspec. A single generic DLT pipeline takes the Dataflowspec and runs your workloads.

• Capture input/output metadata in onboarding file
• Capture Data Quality Rules
• Capture processing logic as sql in Silver transformation file

• Apply appropriate readers based on input metadata
• Apply data quality rules with DLT expectations
• Apply CDC apply changes if specified in metadata
• Builds DLT graph based on input/output metadata
• Launch DLT pipeline

Refer to the Getting Started

Refer to the FAQ and DLT-META documentation

Please note that all projects released under Databricks Labs are provided for your exploration only, and are not formally supported by Databricks with Service Level Agreements (SLAs). They are provided AS-IS and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects.

Any issues discovered through the use of this project should be filed as issues on the Github Repo.
They will be reviewed as time permits, but there are no formal SLAs for support.