
Business Case
Our client, a leading fintech company, enables thousands of financial institutions to engage millions of borrowers with better loan options. Our client was on a mission to expand their analytics platform when they faced a critical block: Their existing platform architecture was at maximum data capacity. To onboard new customers, our client needed a more scalable analytics solution. In addition, our client wanted to enhance their platform’s reporting experience. Existing reporting was limited and required users to export data to Excel for manual analysis, delaying insights. To increase their product value and onboard more customers, our client needed a scalable architecture with embedded reporting.Key Challenges
• Enable analytics platform to scale to 1000+ customers
• Enable self-serve, near real-time analytics
• Enable AI/ML capabilities for future innovation
• Improve security of financial data
Our Solution
We rebuilt our client’s analytics platform using Azure Synapse, Azure Data Lake Storage, Azure Data Factory, Azure Databricks, and Power BI. To ensure operational and technical excellence throughout the build, we followed the five pillars of the Azure Well-Architected Framework and leveraged migration strategies from Microsoft’s Cloud Adoption Framework.Reliability: Implemented query replica within Azure Analysis Services (AAS) to ensure resource intensive queries do not impact ETL processing. Configured secondary and backup resources to ensure 100% resource availability.
Security: Enabled role-based access, disabled public access to storage accounts with PII data to ensure partner data is isolated within the ecosystem. In doing this, we greatly reduced the risk of security threats.