Schema Drift vs. Semantic Drift in Data Pipelines

When a column is removed from a source database or dataset, the next pipeline run usually fails, making the problem easy to detect. But when a field keeps the same name and data type but its meaning changes (known as semantic drift), the pipeline can continue running normally, allowing the problem to go unnoticed. This happens because a schema... Weiterlesen: Schema Drift vs. Semantic Drift in Data Pipelines