The Data Debt Retirement Planner

 Build a Data Debt Retirement Planner that helps engineering teams identify and systematically eliminate accumulated data problems before they become expensive failures. Import data pipeline definitions, schema inventories, data-quality reports, transformation scripts, and incident records. Identify duplicated transformations, undocumented fields, fragile dependencies, inconsistent definitions, obsolete datasets, and recurring manual corrections. Estimate remediation effort, map downstream consumers, and generate a phased cleanup roadmap based on business impact and dependency risk. Allow teams to simulate removing or replacing individual datasets before committing to changes. Explain how each finding was derived, distinguish estimates from measured costs, and never recommend deleting a dataset without checking ownership, retention obligations, and downstream dependencies.