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Transforming data infrastructure how coforge modernized data operations for a leading financial services firm
Transforming Data Infrastructure: How Coforge Modernized Data Operations for a Leading Financial Services Firm
Overview.
A leading financial services firm faced significant challenges with their data management processes, particularly in supporting their legacy policy administration systems. These issues necessitated a comprehensive data modernization strategy to improve efficiency and reduce operational costs.
Challenges.
Prolonged processing times: Sequential job processing times exceeded 10 hours.
Underutilized processing power: Informatica used for ETL jobs failed to harness allocated processing resources effectively.
Excessive data read/writes: Data read from the source was written three times before being pushed to the ODS.
Inefficient reference tables: Large reference table count with non-standard structures.
High data rejection rates: Majority of data records were rejected due to inadequate transformation support.
Lack of audit and control: Insufficient audit, balance, and control mechanisms.
Solutions.
Coforge proposed a comprehensive solution to modernize the firm's data infrastructure by leveraging AWS technologies and advanced ETL frameworks:
Developed a scalable and serverless ETL framework on AWS, replacing Informatica BDM for ETL conversions and downstream extracts.
Created a GraphQL API-based framework to support all extract needs for internal and external third-party applications.
Developed a thin Pyspark ETL framework using AWS Glue to support ETL needs for smaller source systems.
The impact.
50%
Reduction in Time-to-Market: Accelerated the delivery of new systems, marts, and third-party extracts.
80%+
Speed-Up in Data Movement: Significantly faster landing-to-stage data movement.
40%+
Speed-Up in Staging-to-ODS Data Movement: Accelerated the staging to ODS data processing.
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