Data Ingestion with Unity Catalog in Databricks

Data governance and ingestion can quickly become complex when dealing with multiple sources and formats. Unity Catalog solves this by providing a unified governance layer for data and AI on Databricks. This text-only course provides a comprehensive introduction to ingesting data into Unity Catalog. You will learn how to transition from basic file uploads to building automated, secure data pipelines that load directly into managed and external tables. What you'll learn: - Understand foundational Unity Catalog concepts, including metastores, catalogs, schemas, and secure storage locations. - Configure managed connectors to ingest data from relational databases and cloud object storage. - Apply SQL commands and Databricks notebooks to load and structure incoming data. - Implement incremental data loading with Auto Loader to process streaming and batch files efficiently. - Build declarative pipelines using Delta Live Tables to automate data quality checks and transformations. - Practice basic data governance by managing table permissions and tracking data lineage. You will start with key terminology and catalog architecture before exploring step-by-step written guides on batch, streaming, and declarative ingestion methods. This course is ideal for beginner data engineers, analysts, and database administrators who want to build a solid foundation in Databricks data management. No prior experience with Unity Catalog is required. Start reading to build secure, scalable data ingestion pipelines today.