An Integrated Data Warehouse to Identify HIV/AIDS Prevalence

Major advances in the medical domain have led to an increase in biological data. Hence it is becoming difficult to compile such data and use it to extract some beneficial information, A Data warehouse is one of the solutions to compile massive amounts of data in one place and use it for strategic decision-making. The data warehouse development for an enterprise is also beneficial in the aspect that it is a permanent storage space for various data sources which, together in one place, support business intelligence functions, strategic decision-making, reporting, and analysis. Despite data warehouse advantages in the medical domain, there are a few challenges in its development. The prominent involves the fact that data in the medical domain is usually in text format. Different departments in healthcare organizations have unique records for patients. Also, doctors or nurses may use different medical terminologies to record patients’ data. In the medical domain, historical data holds significant importance in predicting the future of diseases; hence it needs to be kept in a non-volatile storage i.e., a data warehouse. HIV (Human Immunodeficiency Virus) has been a deadly disease in human life for many years. Its eradication is a big challenge for physicians, and researchers are also looking for methods to save lives from HIV/AIDS (Acquired Immune Deficiency Syndrome). This paper presents a scalable data warehouse architecture designed for managing HIV/AIDS data. The system enables strategic decision-making by handling heterogeneous data sources and offers improved query performance through OLAP. The purpose of this paper is to build a data warehouse to help in strategic decision-making that is useful for the diagnosis and treatment of HIV patients.