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How a F500 Pharmaceutical Commercial Team achieved Data Democratization and reduced Drug Commercialization Cost by 30%
Highlights
Client Profile
Business challenges
• To migrate their on-premises system to AWS and to rearchitect a commercial data lake and a data warehouse with end-to-end process automation.
• To integrate data across the organization, improve data management, and ensure the availability and democratization of diverse data sets for stakeholders.
• Rigid data silos (CRM, database, and flat files) resulted in lack of view of product movement and sales progression
• Existing architecture was not conducive for near-real time Advanced Analytics
• Lack of Managed services delivery model and governance process for scope management
Agilisium Solution
• A Cloud One strategy to progressively transition to a globally accessible and scalable Big Data Analytics platform was devised.
• To rearchitect a commercial data lake, Amgen leveraged the capabilities of Amazon S3 as the single source of truth and constructed a data warehouse with Amazon Redshift.
• A Massively Parallel Processing (MPP) Analytics Data Warehouse in AWS Redshift that supports downstream BI & Advanced Analytics, at scale
• Faster processing of data with no connectivity issue for business users
• Reduced redundant pipelines to improve performance
• Stabilized the job scheduling using Airflow
• Implemented File Quality & Data Quality to reduce cost automated validation of data
Tech-stacks Used
Business outcome
- Enabled Quicker, faster, and easy access of Data to different stakeholders.
- Reduction of manual effort in data validation
- Source file data validation before job run reduces the error & cost
- Easy error handling & re-run of jobs in case of failures
- Handle large volume of data without any latency
- Quicker data on-boarding without any deviation or delays
- Effective KPIs implemented in Tableau due to consolidated data availability.
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