Introduction
General Electric Health Care faced the challenge of managing diverse source data from hospital equipment, including sensor data and PHI, stored in various formats. They needed a centralized solution on AWS for processing, enriching, and visualizing this data.
Analyzing the Problem
The existing infrastructure was inadequate to handle the increasing demand for processing and analyzing healthcare data. A solution was required to store, process, and visualize diverse data types securely and reliably.
Business Need:
- Centralized storage and processing of diverse healthcare data.
- Scalable infrastructure to handle increasing data volumes and processing requirements.
- Fast and reliable data processing for analytical insights and visualization.
Our Solution
- We implemented a solution on AWS involving multiple services:
- Utilized Amazon S3 for storing source, processed, and enriched data.
- Employed AWS EMR for periodic workloads, utilizing Spark, Sqoop, Hive, Oozie, and Zeppelin for data processing, aggregation, and querying.
- Leveraged Amazon Redshift as a data warehouse for preserving historical data.
- Utilized AWS IoT to collect sensor data and store it in S3 for further processing with EMR.
- Employed AWS EC2 instances for installing custom software for data visualization.
Key Results Achieved
The implemented solution delivered:
- Centralized storage and processing of diverse healthcare data on AWS.
- Scalability to handle increasing data volumes and processing needs.
- Fast and reliable data processing for analytical insights.
- Efficient utilization of AWS services for data collection, processing, and visualization.
Conclusion
General Electric Health Care successfully addressed its data management and processing challenges by migrating to AWS and implementing a comprehensive solution. The solution provided scalability, reliability, and efficiency, enabling them to derive actionable insights from diverse healthcare data sources.
