⋅5 min read
Building data quality checks in your pySpark data pipelines
Data quality is a rather critical part of any production data pipeline. In order to provide accurate SLA metrics and to ensure that the data is correct, it is important to have a way to validate the data and report the metrics for further analysis.
Dan
