M3: implement Data Quality Workbench

Five rule scanners (duplicate customers, missing fields, odometer regression, booking overlap, status conflict) run automatically after seed and via an explicit scan endpoint. Issue defer/reject/merge-customers endpoints with transactional customer merge (booking rewiring, tombstone, audit). Data Quality nav + workbench UI with two-column duplicate comparison and inline (non-native) confirm. Dashboard attention items now link to issues. 35 backend tests passing, ruff clean. Fixed a real false-positive bug in odometer-regression detection found through iteration on seed data, and two TS narrowing errors. Verified end-to-end via browser: S2 merge and S4 overlap scenarios.

frontend/src/pages/Dashboard.tsx

@@ -53,7 +53,9 @@ export function Dashboard() {
               <SeverityBadge severity={item.severity} />
               <div>
                 <p className="attention-title">
-                  {item.link_type === "vehicle" ? (
+                  {item.issue_ref ? (
+                    <Link to={`/data-quality/${item.issue_ref}`}>{item.title}</Link>
+                  ) : item.link_type === "vehicle" ? (
                     <Link to={`/vehicles/${item.link_ref}`}>{item.title}</Link>
                   ) : (
                     item.title