Case Study

Modernizing Enterprise Data Platforms Through Oracle-to-Snowflake Migration

Industry

Wealth Management & Financial Services

Location

United States

Our Contributions

Data Platform Modernization, Cloud Data Warehousing, Snowflake Migration, Data Engineering, Automation & CI/CD, Cloud Governance

Wealth management firms rely on timely, accurate, and scalable data platforms to support analytics, regulatory reporting, and digital innovation. However, legacy on-premises data warehouses often struggle to keep pace with growing data volumes, real‑time processing needs, and modern analytics workloads, leading to performance bottlenecks and rising operational costs.

To improve agility and prepare for future analytics and AI adoption, leading financial services organizations are modernizing their data estates by migrating to cloud‑native platforms that offer scalability, automation, and stronger governance.

The Challenge

The client was operating a legacy on‑premise Oracle data warehouse that lacked the performance, flexibility, and scalability required to support modern analytical and digital data sources. Rising maintenance costs and high operational overheads were further constraining business agility.

Disconnected ingestion and transformation pipelines produced fragmented, inconsistent outputs, while manual, error-prone processes delayed reporting and insight generation. Limited monitoring, lineage, and alerting reduced data trust, and a rigid legacy architecture made it difficult to onboard new data sources, underscoring the need for an enterprise-grade, cloud-native data platform.

Our Approach

Coforge modernized the client’s data estate by designing and implementing a unified, cloud‑native Snowflake platform, supported by Azure‑native services and automated delivery pipelines

Oracle to Snowflake Migration

Assessed and migrated approximately 252 legacy Informatica mappings from Oracle to Snowflake, optimizing logic and performance using Data Object Analyzer and Data Migration Tool accelerators.

Cloud Native Data Platform Foundation

Built an enterprise data platform using Snowflake, Azure Data Factory (ADF), Databricks, DBT Core, Terraform, and Azure DevOps, enabling elastic compute, scalable storage, and modern data engineering workflows.

Automated Ingestion & Transformation

Implemented pattern‑driven ADF ingestion pipelines using the DataFlux artifact, supporting raw‑to‑curated data processing across structured and semi‑structured sources. Enabled robust transformations through DBT Core with automated lineage, validation, and dependency management.

DevOps & Infrastructure Automation

Adopted full CI/CD integration via Azure DevOps for version control and automated deployments. Provisioned end‑to‑end environments using Terraform to ensure consistent, secure, and rapid infrastructure rollout.

Impact to Date

The Oracle‑to‑Snowflake modernization delivered sustainable improvements in performance, efficiency, cost, and data reliability, creating a future‑ready analytics foundation.

20% Faster

Query & Processing Performance

15% Gain

Operational Efficiency

8% Lower

Infrastructure & Platform Costs

30% Reduction

Manual Processes