MASTER OF SCIENCE PROJECT DEFENSE BY: Apeksha Nandkumar Shelke
When: Wednesday,
May 20, 2015
1:00 PM
-
3:00 PM
Where: Science & Engineering Building, Lester W. Cory Conference Room: Room 213A
Cost: free
Description: TOPIC: HEALTHCARE DATA ANALYSIS USING APACHE HADOOP MAPREDUCE
LOCATION: Lester W. Cory Conference Room
Science & Engineering Building (Group II), Room 213A
ABSTRACT:
The healthcare industries along with the IT industries need systems that can collect and process the ever-growing data of patients. Useful knowledge can be extracted from the generated patient data, which can be in the form of patients EMR (Electronic Personal Record) or PHR (Personal Health Record). However, the RDBMS (Relational database management system)-based framework has the limitations to support big healthcare data. In order to address this problem, a massive data management and analysis solution based on Apache Hadoop Mapreduce is considered. The Hadoop technique has been proved to achieve a better performance as it processes the data in parallel and provides data locality, further reducing the computational time. The technique is also fault tolerant and scalable. In the project, the data analysis techniques based on Hadoop and RDBMS are studied respectively. Experimental results show the advantages and disadvantages of both of the techniques, eventually proving that Hadoop is a more effective approach.
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Advisor: Dr. Honggang Wang
Committee Members: Dr. Liudong Xing, Department of Electrical & Computer Engineering and Dr. Jan Bergandy, Department of Computer and Information Science
LOCATION: Lester W. Cory Conference Room
Science & Engineering Building (Group II), Room 213A
ABSTRACT:
The healthcare industries along with the IT industries need systems that can collect and process the ever-growing data of patients. Useful knowledge can be extracted from the generated patient data, which can be in the form of patients EMR (Electronic Personal Record) or PHR (Personal Health Record). However, the RDBMS (Relational database management system)-based framework has the limitations to support big healthcare data. In order to address this problem, a massive data management and analysis solution based on Apache Hadoop Mapreduce is considered. The Hadoop technique has been proved to achieve a better performance as it processes the data in parallel and provides data locality, further reducing the computational time. The technique is also fault tolerant and scalable. In the project, the data analysis techniques based on Hadoop and RDBMS are studied respectively. Experimental results show the advantages and disadvantages of both of the techniques, eventually proving that Hadoop is a more effective approach.
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Advisor: Dr. Honggang Wang
Committee Members: Dr. Liudong Xing, Department of Electrical & Computer Engineering and Dr. Jan Bergandy, Department of Computer and Information Science
Contact:
ECE: Electrical & Computer Engineering Department 508.999.9164 http://www.umassd.edu/engineering/ece/
Topical Areas: General Public, University Community, Electrical and Computer Engineering