USV Leverages AWS Data Lake for Analytics and Business Insights
Introduction
USV is a 61 year old leading healthcare company which began as a joint venture with USV&P Inc. USA, a subsidiary of Revlon. Their product offering today includes Active Pharmaceutical Ingredients (APIs), Fixed Dosages Formulations (FDF), Peptides, Biosimilars and Injectables. These are manufactured in our cGMP compliant plants located in India. USV markets its products globally to 65 countries. USV wants to set up a Data lake on AWS.
Challenges
USV wanted to build a Data Lake platform using AWS services to cope up with the company’s data growth and to make better, faster business decisions while their data is highly secured.
Searce Solution
USV’s Data Source is SAP HANA. Data will be pulled from SAP to S3 using AWS Lambda and reports to be published to around 4k users using Google Sheets.
Searce conducted a Well-Architected Framework Review of their architecture to ensure that the overall architecture is as per the best practices recommended by the AWS. The Searce solution involved:
- Searce used an API to pull data from SAP HANA using AWS Lambda to load them into S3 daily as per the batch schedule
- Searce team created an AWS Lambda function to pull quarterly data from the CSV files and load that into Google Sheet using API
- Created scripts in Google Sheet AppScript editor to get the sheet URL and map the email distribution list
- Send the reports from Google sheets using Google API to the email Distribution List
Business Impact
With the new Architecture design and AWS’ services USV was able to:
- Successful deployment of AWS infrastructure as per best practices adhering compliance requirements (healthcare data protection policy)
- Significant saving on License cost
- Single Data ingestion framework for multiple data domains
- Fully integrated data for quick data processing
- Optimization and operational efficiency
Concluding Quote
The successful implementation of DataLake reduced the issues associated with the data silos enabling quick data processing, single data pipeline and saved time and costs for data analysis. This also improved their business decision making, security and monitoring data flow with no complexity.
Industry: Pharmaceutical
Workload: AWS Networking components, Amazon S3, AWS Lambda
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