• 1)The project is on medical and healthcare .
• 2)It helps to manage functionality and events in healthcare centre.
• 3)Its helps to determine the different patterns which will helps the patient and the hospitals.
• 4)Secure and easy way of storing information of the patient, doctors, patient, Rooms, and Bill payment.
• 5)It helps us to get details to user on regarding the hospitals sorted by their relevance.

• 1)Spark
• 2)Hive Database
• 3)Spark SQL
• 4)Kaggle
• 5)Jupyter Notebook
• 6)HDFS
• 7)Cloudera-V
• 8)GitHub

• Recent Covid-19 Pandemic has raised alarms over one of the most overlooked area to focus: Healthcare Management.
• While healthcare management has various use cases for using data science, patient length of stay is one critical parameter to observe and predict if one wants to improve the efficiency of the healthcare management in a hospital.This parameter helps hospitals to identify patients of high LOS risk (patients who will stay longer) at the time of admission.
• Once identified, patients with high LOS risk can have their treatment plan optimized to minimize LOS and lower the chance of staff/visitor infection. Also, prior knowledge of LOS can aid in logistics such as room and bed allocation planning.

• 1)Spark SQL
• 2)Partitioning
• 3)Pyspark
• 4)Spark Session
• 5)DataFrame

• 1)KARAN JAIN
• 2)MOHAMMED ZAKIKAREEM
• 3)GAURAV MISAL
• 4)TRUPTI CHAUDHARI

This project uses the following license: MIT License