Predicting disease using information integration platform for large data

Abstract

Big Data is owing to the fact that we are creating a massive amount of data every day. Big data is a huge quantity of data that includes all sorts of concept like social media analytics, next-generation data-management capabilities, real-time data, and much more. It contains structured and unstructured data. Dealing with a large volume of data in extracting useful information or knowledge from those big data is infeasible. In many situations, the knowledge for extraction process has to be very well-organized and close to real time since storing all pragmatic data is almost infeasible. The unprecedented data volumes require an effective data analysis and prediction platform to achieve fast response and realtime classification for such Big Data. To explore Big Data, we have analyzed several challenges at the data, model, and system levels. As Big Data are often stored at different locations, the data volumes may continuously grow. So an effective computing platform will have to take distributed large-scale data storage into consideration for computing. The key characteristics of the Big Data are huge with heterogeneous and diverse data sources also autonomous with distributed, decentralized control and complex to evolve in data and knowledge associations. Big Data occupies the medical area in a wide manner. Especially during the period of pregnancy, the blood sugar for women goes up. Gestational diabetes occurs even women who have not had diabetes need treatment for diabetes during the pregnancy. This should be treated with a more frequent checkup. If these are not carried out in a proper manner, then it may lead to a serious problem for both mother and baby. Here we discuss the big data, big data in medicine and the proposed solution lead to maintain the blood-glucose level for pregnancy women by frequent checkup and intimate to their relatives or friends regarding the variations in the blood-glucose level through the Internet connectivity.