case study

Centralized Cloud Native Data Lake


Business Impacts


Reduction in Time to Market


Efficiency in Meeting SLAs

Customer Key Facts

  • Location : North America
  • Industry : Insurance

Problem Context

The client, a large insurance company, stored their data in multiple formats which resulted in data duplicacy. They sought to build a centralized, cost-effective, and scalable data platform hosting for low-latency delivery to enterprise customers around the world with self-service BI capabilities.



  • Use of Different Data ingestion and ETL techniques for streaming and historical data
  • Due to GDPR and compliance issues data lake had to be built in the Ireland region on AWS
  • Business had around 1600 tables and a lot of attributes to work with for reporting
  • Absence of proper Data dictionary and Data Lineage tracking feature


Amazon Redshift

Amazon Redshift

Amazon S3

Amazon S3

Amazon EC2

Amazon EC2

Amazon DMS

Amazon DMS

AWS Lambda

AWS Lambda

Migrated data from multiple on-site data sources to the cloud and established a centralized data lake platform


Quantiphi helped the client migrate data from multiple on-site data sources to the cloud and established a cost-effective, scalable, and centralized data lake platform on the cloud by setting up an intake pipeline with security protocols and enabled them to view and gain insights in real-time.


  • Built a cost-effective Data Lake enabling faster insights and time to market
  • Less Delays in Data Processing, ETL Jobs, and BI Reporting



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