Data metrics in public health programs and interventions play a crucial role in reflecting the health and well-being of the population, along with the structural and biosyndemic factors influencing health, public health interventions, and system resources. The management of health data has emerged as a key focus area within the sustainable global agenda, aiming to ensure effective, efficient, timely, and safe quality healthcare through evidence-based clinical practices and high-quality data systems that support quality improvement strategies and interventions to achieve optimal standards of care. Recognized internationally as an integral part of the unfinished health goals and the Sustainable Development Agenda 2030, a high-quality health information system is deemed essential for positively impacting health outcomes. However, emerging economies like India face the significant challenge of developing complex data platforms to track SDG health goals effectively, thereby providing useful insights for policymakers, academics, researchers, and program implementers. This paper aims to contribute to the growing knowledge on the implications of poor data quality and the performance of health information systems. It outlines the availability, completeness, and accuracy of data related to key performance indicators in the maternal and child health domain, evaluates the capacity and readiness of healthcare systems to generate high-quality data metrics, and explores the challenges, determinants, and gaps in achieving a sustainable and effective data management system. The study utilizes a mixed-methods approach and the WHO-DQAT data quality framework, employing objective-subjective assessments, desk analysis, cross-sectional field validation surveys, and integrated mixed-triangulation data tools. By measuring data quality dimensions and identifying potential gaps and determinants, the paper sheds light on deficiencies in the structure, function, and capabilities of the system, particularly in data management processes. It emphasizes the importance of strengthening statistical capacities and creating dedicated data management systems at state and national levels, and urges stakeholders to recognize the significance of data in health information systems for evidence-based policymaking.