Data Modernization on Azure Cloud
InsuranceBusiness Impacts
Scalable & flexible data storage and compute for 2000+ objects (3+ TB of data)
Faster data accessibility for reporting & analytics with processes finishing every 1 hour
Customer Key Facts
- Industry : Insurance
- Country : US
Problem Context
The client is a Fortune 500 Company providing insurance and other services. Due to the rigidity of the legacy data system, the data could not be leveraged for analytics & data science purposes. The client wanted a flexible, data lake on cloud-enabled with analytics capabilities to improve productivity and decision making.
Challenges
- Scalability limitations & high maintenance of on-premise data stores
- Lack of technical infrastructure to support data science solutions
- Significant manual work & data correction while creating reports
- Poor Data Governance
- Legacy technology impacting user experience & productivity
Technologies Used
Azure DevOps
Azure Data Factory
Azure Pipelines
Azure Active Directory
Azure Data Bricks
Snowflake
Microsoft PowerBI
Solution
Quantiphi created a cloud-based data platform set up to bring the data from various on-premise systems and data sources to Azure Cloud using Azure Data Factory. Quantiphi also set up a Data Lake and Delta Lake for prioritized sources, including the complex merger of historical data with incremental data. This established Snowflake as an enterprise data warehouse and implemented fine-grained data governance and security considerations.
Results
- Enabled their advanced analytics & data science with Azure Cloud Native components.
- Solid Data Governance & role based accessibility
- Improved Data Quality & Security
