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Business Impact

  • 70%

    Reduction in Time to Market

  • 77%

    Less Delays in Data Processing, ETL Jobs and BI Reporting

  • 95%

    Meeting SLA Efficiency

Customer Key Facts

  • Location : North America
  • Industry : Insurance

Problem Context

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

Challenges

 

  • 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 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.
Challenges

Technologies Used

Amazon EC2
AWS Lambda
Amazon Redshift Spectrum
Amazon DMS
Amazon Kinesis
Amazon SQS
Amazon SNS
Amazon S3
Power BI

Solution

Quantiphi helped them 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 enabling them to view and gain insights in real time

Result

  • Successfully built a cost effective Data Lake for a quicker delivery to customers around the world
  • The solution was able to reduce the time to market by 70%

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