A Review of Diabetes Diagnosis and Record Management using HIVE

Modernizing healthcare industry's move towards processing massive health records, and to access those for analysis and put into action will greatly increases the complexities. Due to the growing unstructured nature of Big Data form health industry, it is necessary to structure and emphasis its size into nominal value with possible solution. Healthcare industry faces many challenges that make us to know the importance to develop the data analytics[1].In this paper we will show that how HIVE (hierarchy of international vengeance and extermination) can process and analyze the diabetic data set with the help of SQL like HIVEQL. With the help of HIVE complexity is reduced. No need to write big and complex programs in java. HIVE structures the data and also queries the data in a very small amount of the time. It can manage only big data. For small data HIVE is not applicable. It supports data loading. This language supports tables, partitions, join, aggregation etc. HIVE also includes a system catalog- Metastore that contains schemas and statistics which are beneficial in data processing, data analyzing, query optimization and query compilation. Analyses of the diabetic data to perform the Outpatient Monitoring and Management of Insulin Dependent Diabetes Mellitus (IDDM) set using HIVE as a warehousing tool resulted in providing an efficient way to cure and care the patients and in deriving some interesting facts such as helping the hospital management to manage the patient records and arrange the medical equipments, staff, labs etc based on the frequency of the arrival of the patients on daily, monthly as well as yearly basis.