Generate relevant synthetic data quickly for your projects. The Databricks Labs synthetic data generator (aka `dbldatagen`) may be used to generate large simulated / synthetic data sets for test, POCs, and other uses in Databricks environments including in Delta Live Tables pipelines

A lightweight helper utility which allows developers to do interactive pipeline development by having a unified source code for both DLT run and Non-DLT interactive notebook run.

The Metadata Driven framework for Databricks Lakeflow Declarative Pipelines (formerly Delta Live Tables). Metadata framework that generates production ready Pyspark code for Lakeflow Declarative Pipelines

Databricks DLT Apparel Pipeline Project: Learn medallion architecture, streaming, and data engineering with Delta Live Tables. Includes synthetic data, step-by-step guide, and certification prep.

Schema mappings in SQL and PySpark for ELT pipelines to normalize data to OCSF

Real Estate ELT pipeline using Databricks Asset Bundles on GCP. Ingests, transforms, and analyzes property data via Delta Live Tables. Follows medallion architecture (Bronze/Silver/Gold), modular Python design, CI/CD automation with GitHub Actions, and full Unit and Integration tests coverage.

Azure ADF + Databricks (Delta Live Tables) Medallion pipeline for Netflix data — Bronze→Silver→Gold with Unity Catalog & Power BI.

A library for authoring DLT pipelines via meta-programming patterns and deploying to Databricks workspaces.

End-to-end sales data warehouse built with Databricks Delta Live Tables. Features automated ETL, change data capture, and medallion architecture. Transforms raw multi-region sales data into analytics-ready dimensional models.