Helped a leading pharma client to hasten their decision making by leveraging the power of cloud
The client is a leading pharmaceutical company based in the United States.
The client wanted to streamline their data management process by bringing in optimal tech stack for processing Petabytes of data, a better process for data sharing, and enable higher consumption of data across the organization.
- The current tech stack had a higher processing cost and the speed was not in the expected lines, due to which the client was not able to leverage the power of ML models to the fullest
- Scalability was a challenge in the current system, accessibility and data sharing was one of the key challenges
- The current system was not able to handle the volume of data
- Data was stored in silos posing challenges for business for a common taxonomy
- AWS-Migrate identified sources on AWS and build DevOps capabilities
- Snowflake-Cloud Datawarehouse to host seamless data
- Data Consumption- Tableau, Jupyter Notebooks, Data IKU
- Explored 10+ cloud technologies, performing quick POV’s demonstrating scalability and effort distribution
- Initiated data pipeline build using AWS, Snowflake and Talend
- Enabled all legacy system migration into snowflake along with analytics consumption using Tableau, Jupyter Hub, Data IKU, Analytical data marts
- Data enablement hastens decision making and workforce is now able to meet objectives around customer engagement through rich analytical solutions
- Business teams were able to focus on Insights /customer engagement rather than data enablement.
- Cost efficiency was realized, and data consumption helped the client realize new market revenues
- Several data products and applications rolled out in a short span
- Seamless integration and data sharing achieved enabling cross-functional insight generation
- Scalable cloud platform reduces data silos and easy adoption by end-users
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