This chapter advances from traceability to reliability. It reframes data quality as a continuous engineering discipline and introduces measurable reliability contracts aligned with lifecycle boundaries. Quality enforcement is modeled as a system-level control function rather than episodic validation. The chapter defines yield metrics and threshold policies as operational indicators and presents a case study involving automated containment mechanisms that isolate unstable data flows. By integrating reliability engineering concepts into data infrastructure design, the chapter establishes protection mechanisms necessary for safe automation and AI augmentation.