Global bank accelerates multi-system lineage tracking with Code Harbor™
A leading global bank operated in a high-volume, data-intensive environment. To stay competitive and compliant, they committed to an enterprise initiative aimed at boosting operational transparency and efficiency. Achieving a seamless view of multi-system data lineage became a critical priority, yet their existing tools fell short of meeting necessary requirements.
Challenge
The client’s enterprise systems comprised diverse technologies, including Cobol, Java, PySpark, and SAS. Their existing data governance tool was unable to effectively track transformations and relationships between these technologies, leading to operational bottlenecks and inefficiencies. Key obstacles included:
- Lack of transformation mapping: The inability to track variable transformations across code files and systems created knowledge gaps.
- Complexity of diverse technologies: Managing granular data lineage consistently across multiple coding environments with unique rules proved challenging.
- Manual effort and delayed insights: The manual process of tracing data lineage consumed significant time and resources, delaying decision-making and system integrations.
This lack of actionable insights in tracking data’s origin slowed business operations and hindered the ability to ensure compliance across units.
Solution
EXL’s Code Harbor™, a generative AI-powered platform, addressed the bank’s challenges comprehensively through advanced automation, modularity, and customization. Key components of the solution included:
Technical lineage generation at scale
Code Harbor seamlessly generated technical lineage across Cobol, Java, PySpark, and SAS codebases, providing a holistic view of transformations across each system.
- Enabled clear identification of variable sources, transformations, and dependencies within and across code files.
- Mapped transformations for each variable hop in record time, ensuring accuracy at an unprecedented scale.
Flexible output formats
The solution delivered output in visual diagrams, JSON, and CSV formats, ensuring Global Bank could integrate insights into their existing workflows and systems with ease.
Enhanced workflow optimization
Code Harbor effectively automated lineage tracking and significantly reduced manual effort. Its multi-agent framework identified data transformations quickly and maintained the context of complex code files.
Scalable and modular design
Leveraging an open and cloud-agnostic AI architecture, Code Harbor adapted to the bank’s existing infrastructure. Customization options ensured seamless alignment with internal systems and compliance considerations.
By integrating Code Harbor, EXL’s client gained a unified and scalable enterprise-grade solution specifically built to meet the complexities of multi-technology environments.
Results
The implementation of Code Harbor produced measurable improvements for the bank, transforming the way they managed and analyzed data lineage. Key outcomes included:
- 70% faster lineage identification
Code Harbor accelerated the process of identifying data and variable origins, enabling the client to reduce delays in operational workflows.
- One-stop solution for diverse technologies
The solution provided a unified platform capable of managing data lineage seamlessly across Cobol, Java, PySpark, and SAS, eliminating the need for multiple disparate tools.
- Flexible output generation
Delivering outputs in visual, JSON, and CSV formats allowed for the client to seamlessly consume and leverage insights based on their specific requirements. These results not only enhanced operational efficiency but also positioned the bank to meet their compliance and governance goals more effectively.