www.rspsciencehub.com Volume 03 Issue 07S July 2021 International Research Journal on Advanced Science Hub (IRJASH) 42 Special Issue of Second International Conference on Advances in Science Hub (ICASH 2021) Big Data Analysis and Management in Healthcare Madhamsetty Charitha 1 , Nagaraj G Cholli 2 1 Department of Information Science and Engineering, RV College of Engineering, Karnataka, India. 2 Assistant Professor, Dept. of Information Science and Engineering, RV College of Engineering, Karnataka, India. madhamsettyc.is18@rvce.edu.in 1 , nagaraj.cholli@rvce.edu.in 2 Abstract Basically, Big Data means large volumes of data that can be used to solve problems. It has piqued people’s attention over the past two decades because of the enormous potential it holds. Big data is generated, stored, and analyzed by a variety of public and private sector industries in order to enhance the services they provide. Hospital reports, patient medical records, medical test outcomes, and internet of things applications are all examples of big data outlets in the healthcare industry. Biomedical research often produces a large amount of big data that is pertinent to public health. To extract useful information from this data, it must be properly managed and analyzed. Otherwise, finding solutions by analyzing big data quickly becomes impossible. The ability to identify trends and transform large amounts of data into actionable information for precision , medicine and decision makers is at the heart of Big Data’s potential in healthcare. In a variety of areas, the use of Big Data in healthcare is now offering solutions for optimizing patient care and creating value in healthcare organizations. In this paper, some big data solutions are provided for healthcare. Big Data Analytics strategies to mitigate covid-19 health disparities are provided. Finally we analyse some of the challenges with big data in healthcare. Keywords: Big Data, Electronic Health Records(EHRs), Healthcare, Internet of things(IOT), Machine Learning, Hadoop, Apache Spark, Medical Imaging, COVID-19 1. Introduction 1.1 What exactly is Big Data? The word "big data" refers to the data which is so massive, quick, or complex that processing it with conventional methods is difficult or impossible. The practice of accessing and storing vast volumes of data for analytics has a long history but the “big data” concept gained momentum in 2000’s. Big data can be described in five V’s i.e there are five characteristics of big data. Volume – Volume refers to size of data. The term “BigData” itself refers to enormous size. So, to consider some data as big data, it’s volume must be large. The data collected by an organization is generally huge. They collect data from various sources like business transactions, videos, social media, industrial equipment etc. Example: The global mobile traffic, estimated in the year 2016, was 6.2 billion GB of data each month. By the year 2020 it is 40000 billion GB of data. Velocity – The term "Velocity" refers to the rapid accumu- lation of data. Data comes in at a high rate from machines, networks, social media, cell phones, and other outlets in Big Data velocity. A vast and rapid flow of data exists. This influences the data's potential, or how quickly data is produced and analyzed in order to fulfil demands. Example: On google, almost 3.5 billion inquiries are made in the world each day. Likewise, clients of FaceBook are expanding by 23% every year.[1-4].