Big data analytics has helped healthcare improve by providing personalized medicine and prescriptive analytics, clinical risk intervention and predictive analytics, waste and care variability reduction. Automated reporting of patient data, standardized medical terms, and patient registries. The level of data generated within healthcare systems seems trivial, but with the adoption of mHealth, eHealth, and wearable technologies, the volume of data will continue to increase. This includes electronic health record data, imaging data, patient-generated data, sensor data, and other forms of difficult-to-process data. There is now an even greater need for such environments to pay greater attention to data and information quality. Big data is dirty data, and the fraction of data inaccuracies increases with data volume growth. Human inspection at the big data scale is impossible, and there is a desperate need in health services for intelligent tools for accuracy and believability control and handling of information missed. Yet in SA, extensive information in public healthcare is not electronic; it fits under the big data umbrella because it is unstructured and difficult to use. The paper adopts a qualitative case study approach to explore and explain the role of big data in the South African Public Healthcare.