Databricks Certified Data Engineer - Associate

Delta Live Tables is the correct tool for automating data quality monitoring in data pipelines. It provides several key features:

1. Data Quality Expectations: Delta Live Tables allows data engineers to define expectations (constraints) on data quality that are automatically validated during pipeline execution.

2. Automated Monitoring: When expectations fail, Delta Live Tables can be configured to take actions such as quarantining bad records, failing the pipeline, or logging issues.

3. Data Lineage Tracking: It tracks data lineage throughout the pipeline, helping identify where quality issues originate.

4. Alerting: Can send alerts when data quality checks fail, enabling proactive monitoring.

5. Declarative Framework: Provides a declarative approach to building and managing data pipelines with built-in quality controls.

Why other options are incorrect:

• Unity Catalog: Primarily for data governance, access control, and metadata management, not specifically for automated data quality monitoring.
• Data Explorer: A tool for exploring and visualizing data, not for automated quality monitoring.
• Delta Lake: Provides ACID transactions and schema enforcement but doesn't have built-in automated quality monitoring features like Delta Live Tables.
• Auto Loader: Automates file ingestion but doesn't include comprehensive data quality monitoring capabilities.

Delta Live Tables' expectations feature specifically addresses the requirement to automate quality monitoring as data flows through the pipeline.