Business Impact

  • 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.


  • 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

Microsoft PowerBI


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.


  • Enabled their advanced analytics & data science with Azure Cloud Native components.
  • Solid Data Governance & role based accessibility
  • Improved Data Quality & Security

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