Situation
Our client, a large insurance company in Singapore has a unified data platform (UDP) that serves as its data foundation for operational efficiency, data quality, and data governance. Finance dashboards, regulatory compliance tracking, and AI/ML-driven segment tagging are a part of this on-premise platform.
Migration to the Azure platform lowered infrastructure costs and provided scalability.
Our client wanted to migrate legacy reporting applications from an existing database and decommission them.
Other migrations included SAS ETL jobs and internal data, along with historical snapshots. Data from IBM Netezza and a local data reporting repository also needed redirection to the new platform.
Action
After auditing our client's existing SAS scripts and performing a detailed analysis, we migrated all legacy reporting apps, processes and the existing database to an Azure Cloud platform.
We migrated the SAS code to Databricks Notebooks using Scala or PySpark. Azure Data Factory (ADF) pipelines were configured to run Databricks notebooks, passing the necessary input and output parameters. The pipeline ensured that the data was successfully loaded from the source database and transferred to SQL and databases while also incorporating audit columns.
IBM Netezza components were analyzed, and an Azure-compatible solution was designed. Testing ensured data and report level validations between Netezza and Azure.
We developed Azure Data Factory pipeline and Databrick scripts for insurance modules. Migration of SAS ETL jobs was converted to Apache Spark on Databricks and managed by Azure Data Factory.
The Azure platform handles diverse use cases, supports AI/ML-driven applications, and integrates with new features and micro products for future growth.
Results
- Scalability and lower infrastructure costs with migration to Azure platform.
- Streamlining operations reduced data silos, and improved data management and analytics.
- Real-time data access enhanced reporting, analytics and decision-making.
- Automated leads generation provides a seamless user experience and timely insights.
- Governance and accessibility were improved with a centralized data repository.
Reporting, analytics and decision-making were improved with real-time data access.
Automated leads generation gave the sales team a seamless user experience.
The Azure platform integrates with new features and micro products for future growth.
Reporting, analytics and decision-making were improved with real-time data access.
Automated leads generation gave the sales team a seamless user experience.
The Azure platform integrates with new features and micro products for future growth.
Reporting, analytics and decision-making were improved with real-time data access.
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30%
Reduced infrastructure costs -
-
100%
Compliance with data governance policies -
-
40%
Governance and accessibility improvements