Our client, an American multinational company serving the combined industries of healthcare IT solutions and clinical research, had to deal with unfathomable amounts of data. Their legacy Enterprise Data Warehouses were equipped to handle, store and retrieve structured data, but were not designed for real-time analytics or data transformation. We designed a multi-level program to re-platform the data factory with technologies like Hadoop and Spark. It enabled improvements in data acquisition, processing, warehousing and access.
The following business outcomes were delivered:
- Cost Efficiency: Using multi-tenant platforms, open source, large-scale software like Hadoop and extensive machine learning to process and analyze data
- Flexibility and Scalability: Built a unique data analytics platform and made data available from across more than 15 countries (and counting) on a low-cost storage platform
- Faster Time-to-Market: Reduced the time taken to generate country-level analytics from 4-6 weeks to a mere 6 hours
- New Revenue: The client could leverage the API Economy, which in turn generated further revenue in newer areas
