Client Overview
Our client is a major global insurance provider with a wide range of insurance products. They faced inefficiencies due to outdated manual processes for managing employee data and complex transformations. To enhance operational efficiency and data management, they sought to automate these processes and modernize their infrastructure. The goal was to implement a scalable Azure-based solution to streamline workflows and support their business growth.
Challenge or Business Objective
- Manual Process Automation: The client had a manual process that had been in place for 9 years, which needed to be automated.
- D&B Process Optimization: The process for managing and identifying new employees, which took 3 days, needed to be reduced to 30 minutes.
- Data Migration and Transformation: Required complex data migration, transformation, and Change Data Capture (CDC) for on-premises data.
Strategy or Solution
- Full Process Automation: Automated the entire process that had been manual for nearly a decade.
- D&B Automation: Reduced the time for D&B process automation from 3 days to 30 minutes.
- Data Migration and Transformation: Migrated all data, performed complex transformations, and implemented CDC for ongoing data updates.
Development Method - Execution Method
- Support Model:Established a support model to manage Azure infrastructure and operationalize the environment.
- Data Automation: Developed end-to-end notebooks and scripts for automating data transformation and migration from on-premises to Azure cloud.
- D&B Automation: Created automated workflows for D&B recognition, replacing the previous manual process.
- DevOps Setup: Implemented CI/CD pipelines for smooth code deployment across multiple environments (Dev, QA, UAT, Prod, DR).
- Azure Technologies: Utilized Azure Databricks, Azure Data Factory, Azure SQL/Synapse, Azure Key Vault, Azure Functions, and Azure Data Lake Gen 2.
Impact We Made
- Increased Efficiency: Automated processes reduced manual effort and time, significantly improving operational efficiency.
- Faster Processing: D&B process time was cut from 3 days to 30 minutes.
- Enhanced Data Management: Streamlined data migration and CDC processes facilitated better data handling and accuracy.
- Scalability and Flexibility: Provided a scalable and reliable platform to meet the organization's growing demands.
Tech Strategy
- Azure Data Factory: Used for data migration and transformation.
- Azure Databricks and SQL/Synapse: Enabled advanced analytics and data management.
- CI/CD Pipelines: Ensured smooth deployment and synchronization of code across environments.
- Lifecycle Management: Implemented best practices for managing and securing data with Azure Key Vault and Azure Data Lake Gen 2.
Conclusion:
The project successfully modernized the client’s data management processes, reducing manual efforts, accelerating operations, and improving data accuracy. The integration of Azure technologies provided a scalable, efficient, and secure platform that met the client’s evolving needs.
