Setting up the Analytics on Azure & AWS
Background
Our client is a a research and development company focused on oncology treatments, improving access focused on helping patients across China, US and EU.
Key Issue
data feeds was looking for an improvement in the following -
• Generate and process on-the-fly Adhoc reports on multitudes of research issues. E.g. How reliable the trial data is, how valid is the second and third party data etc.
• An improved response time of On-cloud generated reports.
• Automated Anomaly detection in trial data, as well as first, second and third party data.
Solution
We architected and implemented their BI solution constituting of Big Data and OLTP, with Horizontally shared Azure DWH Analytics and Data Lake.
• Right from defining the project plan we have been responsible for setting up right tools and practices automated with Azure Devops. We integrated Data Bricks, Data Factory and Polybase with Synapse Analytics to build state-of-the-art automated Analytics Based Data warehouse solution that can process records even with drifting and SCD sources.
• At infrastructure level we have designed it futuristic in term of next gen Data warehouse that is horizontally scalable and Multicloud oriented eg. We have integrated AWS S3, Azure Blob, SAP APIS, Custom Source and Data Lake in the same platform.
