Most enterprise data problems are not caused by machine learning models or dashboard tools. They usually start much earlier in the pipeline.A reporting table misses records after a schema change. A nightly ingestion job finishes successfully but loads duplicate transactions. A downstream dashboard suddenly shows a 30% increase in revenue because one transformation joined datasets incorrectly. These issues are common in large-scale analytics environments where pipelines evolve faster than governance processes.