Streamline Data Pipelines: How to Use WhyLogs with PySpark for Data Profiling and Validation

Streamline Data Pipelines: How to Use WhyLogs with PySpark for Effective Data Profiling and Validation

Data pipelines, made by data engineers or machine learning engineers, do more than just prepare data for reports or training models. It’s crucial to not only process the data but also ensure its quality. If the data changes over time, you might end up with results you didn’t expect, which is not good.

To avoid this, we often use …

data engineering data profiling data quality data science pyspark