Data Quality Use Case: How to Test Data Quality in a Databricks Pipeline

A technical product showcase designed for Data Engineers, Scientists, and Analysts, where we’ll explore how to embed data quality checks in your Databricks environment.In this 45-minute webinar, you'll learn how to integrate Soda into your workflows to catch and resolve data quality issues before they affect production. Discover how Soda can help you: - Implement data quality checks directly in your Databricks pipelines - Detect and address issues proactively to maintain high-quality data - Ensure your data pipelines deliver trusted, reliable data products In part 1: Data Engineers will see how to define data quality checks entirely as-code within notebooks, scaling testing and catching issues early. In part 2: Data Scientists and Analysts will learn how to catch data quality issues after ingestion or transformation, using Soda to ensure models don’t train on poor-quality data. Docs Use Case Guide: https://docs.soda.io/soda/quick-start-databricks-pipeline.html