Challenges
In the EDW modernization program, data quality and data catalogue pose significant challenges for HDFC Life Insurance. The organization manages vast and complex datasets across policy administration, claims, distribution, regulatory reporting, and digital channels. Key issues include:
Data Quality Challenges
- Inconsistent identifiers for customers, policies, and intermediaries across legacy systems leading to duplication and reconciliation gaps.
- Incomplete or inaccurate attributes (e.g., policy details, KYC fields, claims status) impacting downstream analytics, compliance, and risk reporting.
- Lack of standardized business rules for validation, creating multiple versions of truth across business functions.
- Data latency and errors in integration from core insurance systems to the warehouse, affecting timeliness of insights.
Data Catalogue Challenges
- Absence of a unified metadata repository, making it difficult for business users and IT teams to discover and trust datasets.
- Limited visibility into lineage and ownership of data elements, which hampers impact analysis and regulatory compliance (e.g., IRDAI reporting).
- Siloed documentation practices, resulting in poor knowledge sharing and heavy reliance on SMEs for data interpretation.
- Difficulty in harmonizing technical metadata with business glossaries, reducing adoption of self-service analytics.
Solutions
To address these challenges, the insurance provider implemented a products from Talend technologies:
Talend Data Quality: To ensure clean, accurate, and cleaned customer, policy, and claims data – driving trusted insights and compliance.
Talend Data Catalogue: To provide a single source of truth with data lineage, business glossary, and ownership – enabling faster discovery and self-service analytics.
Outcomes
- Improved Data Trust – Accurate, complete, and deduplicated customer and policy data across systems.
- Faster Insights – Business users can quickly discover and understand data, reducing dependency on IT.
- Operational Efficiency – Reduced time spent on reconciliation and error correction, enabling focus on analytics and decision-making.
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