case study

Data Modernization on Azure Cloud

Insurance

Business 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 DevOps

Azure Data Factory

Azure Data Factory

Azure Pipelines

Azure Pipelines

Azure Active Directory

Azure Active Directory

Azure Data Bricks

Azure Data Bricks

Snowflake

Snowflake

Microsoft PowerBI

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

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