Financial Information Hub for Claims Analytics

insurance

Client

Large US health insurance

Client is one of the largest health insurers in the USA.

Solution

Cost-effective & scalable framework

  • Datametica created a cost-effective and scalable framework for their financial information hub to acquire, clean, and prepare data for Enterprise consumption;
  • Established a layered data lake/Hub architecture on Hadoop to provide the flexibility to store and process unlimited data;
  • Data was loaded from source data subject areas, processed in Hadoop, and then exposed for analytics;
  • Kafka, Storm, Camus, and Hbase was used for real-time data collection and data aggregation;
  • Gold data tables are exposed to Hadoop SQL interface to enable business users to query;
  • Data governance support with an audit process, metadata management, and data lineage.

Benefits

scalability
Improved scalability

The use of distributed processing power of Hadoop framework led to greatly improved scalability compared to Teradata

 

 

security
Improved security

Improved security and fault tolerance

 

 

tracking
Real-time data

Real-time data views for proactive analysis

 

 

folder
Data ingesting

Ingest of both structured and unstructured data

 

 

costsavings
Reduced costs

Costs reduction compared to legacy Teradata data warehouse approach

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