Modernizing BFSI Data Infrastructure with a Scalable Lakehouse
Migrated a legacy data warehouse to a modern lakehouse architecture for a leading financial services firm, achieving 3x faster query performance and 50% cost reduction.
Company
Private Limited
Domain
BFSI
Service
Data Lakehouse Migration
Technology Stack
Problem Statement
Legacy Data Infrastructure Limited Scalability and Business Insights
The organization's legacy data environment struggled to support growing BFSI data volumes and evolving analytics requirements. Slow ETL processes delayed reporting, while fragmented data silos made it difficult to maintain consistent and governed information. Business teams lacked timely access to trusted data and actionable insights, limiting effective decision-making and self-service analytics. The organization needed a scalable, unified data platform to modernize data processing, strengthen governance, and accelerate analytics.
Key challenges included:
- Legacy infrastructure unable to efficiently handle growing BFSI data volumes.
- Slow ETL pipelines delaying reporting and analytics.
- Fragmented data silos without a unified governance layer.
- Business teams lacking timely access to insights for decision-making.
The solution included:
- Databricks Lakehouse migration.
- Delta Lake architecture.
- Unity Catalog for centralized governance.
- MLflow for model lifecycle management.
- Power BI self-service analytics and executive dashboards.
Solution
Migrating from Legacy Data Silos to a Modern Lakehouse
Peramal implemented a Databricks Lakehouse architecture using Delta Lake to create a scalable and governed data foundation.
Impact & Benefits
Key Benefits Delivered
- 60%+ reduction in data processing time.
- Replaced fragmented legacy systems with a unified Delta Lake architecture.
- Established a centralized governance layer using Unity Catalog.
- Enabled data sharing and compliance.
- Delivered self-service BI dashboards for real-time executive insights.
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