Data Quality as part of the Data Pipeline

Too many data pipelines generate outputs with no consideration for the QUALITY of the data generated. In this presentation, Sandy Ryza (lead engineer on the open-source Dagster project) argues that the orchestration layer is uniquely placed to understand, define, and act on data quality checks.
Join Sandy for a deep dive into how data quality checks should be a first-class citizen in any data platform, and are a natural fit for delivering high-quality data to the organization, reducing computing costs, and improving the observability and debugging of your data pipelines.
00:00 On data pipelines and data quality
02:29 What are data quality checks?
06:15 Defining data quality checks
10:59 Executing data quality checks
13:02 Observing data quality checks
15:12 Alerting on data quality checks
16:36 Asset check patterns
21:31 Conclusion
You can explore data quality checks for free with a 30-day free trial of Dagster hosted on Dagster Cloud: dagster.io/lp/dagster-cloud-trial