Streamlining data processing and efficiently analyzing data through a data warehouse solution
Non-profit healthcare insurance provider migrates to Amazon Redshift to better manage high volumes of data with the help of Cloudtech
About
A non-profit healthcare insurance provider that encountered difficulties in managing the high volume of data on their on-premises system, which impeded their capacity to analyze that data efficiently to make informed business decisions. To address these issues, they chose to migrate their data to Amazon Redshift.
Business Challenge
As their business grew, the insurance provider faced several challenges with their legacy system. Most importantly, their on-prem data warehouse, Oracle Exadata, required significant time and resources to administer, especially for large datasets. Additionally, the financial costs associated with building, maintaining, and growing self-managed, on premises data warehouses are very high.
In order to manage costs, keep ETL complexity low, and deliver acceptable performance, the customer had to constantly trade-off what data to load into the data warehouse and what data to archive in storage.
Technical Challenge
The customer’s data pipeline followed a collect, store, process/analyze, and consume model, leveraging multiple AWS services. Their data lake was created in an Amazon S3 bucket, and the data lake's stored data can be queried using dbt, utilizing AWS Glue Data Catalog Databases and Crawlers.We recommended Amazon Redshift and Redshift Spectrum to build their data warehouse. After mapping the data with Redshift Spectrum, Amazon Redshift processes the data to Redshift tables. Data is then visualized and consumed by users through Amazon QuickSight.
AWS Services Adopted for this Solution
- Amazon S3, for data lakes
- AWS Glue, as a data datalog
- Amazon Redshift, as a data warehouse
- Amazon Quicksight, for data visualization
Data Processing Solution for Healthcare Organization
Amazon Redshift's scalability and flexibility make it easy to manage expanding data volumes effortlessly. With Redshift, customers can reduce their total cost of ownership (TCO) associated with database environments. Redshift also provides a centralized and secure data storage solution, that also automatically patches and backs up the data warehouse, storing backups for a user-defined retention period. This replication and continuous backups enhance availability and improve data durability, and can automatically recover from component and node failures.
Amazon Redshift’s parallel processing and compression capabilities accelerate command execution, enabling it to operate on billions of rows simultaneously. Redshift Spectrum integrates seamlessly with other AWS services (such as Glue), making it easy to build end-to-end data pipelines. This ensures that data is always up-to-date, accurate, and secure.
“Before moving to Amazon Redshift, our engineering team was spending too much time managing our on-prem data warehouse. Now, we are saving so much time on data management, and our data analysis has improved significantly.”
- CIO, Healthcare Insurance Provider
Data Processing Results
With Amazon Redshift and additional AWS services, the customer gained a centralized and secure data storage solution, and a streamlined data analysis process. The scalability and flexibility of Redshift empowered the customer to handle expanding data volumes seamlessly.
Get started with Healthcare Data Processing
Take the first steps to improve your healthcare data processing to see increases in data security, analysis, and scalability. Contact Cloudtech today.