Cloud Data Warehouse Migration

Case Studies

Cloud Data Warehouse Migration

We migrated a massive multi-terabyte Oracle data warehouse into the AWS cloud ecosystem, without losing data integrity or interrupting ongoing operations.

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Client Challenge

A long-standing enterprise client operated a massive multi-terabyte Oracle data warehouse that had become increasingly difficult and expensive to scale. With evolving business demands and the need for faster analytics, the organization sought to modernize its infrastructure by moving fully into the AWS cloud ecosystem—without losing data integrity or interrupting ongoing operations.

Business Ask

“Can you take a multiple-terabyte Oracle data warehouse and migrate all code and data into AWS?”

Full Tilt Data was engaged to lead a comprehensive migration effort—modernizing the client’s data environment, translating legacy code, and rebuilding automation frameworks to function seamlessly in the new cloud-native stack.

Solution

Full Tilt Data designed and executed a large-scale migration plan combining data modernization with process automation:

AWS provided the cloud foundation for scalability and secure storage.
Databricks was leveraged for data processing, orchestration, and validation workflows.
Snowflake served as the new data warehouse platform.
Delta Lake offered optimized data storage and version control during and after migration.
Oracle served as the legacy system from which all data and logic were extracted and translated.

Implementation Highlights

We enforce strong data governance principles to ensure data meaning and integrity.

Massive Data Migration: Transferred 100+ terabytes of structured and semi-structured data from Oracle to Snowflake with zero data loss.
Code Conversion: Translated complex PL/SQL procedures, functions, and packages into Snowflake-compatible stored procedures.
ETL Automation: Rebuilt all Oracle job schedules into Snowflake Tasks, ensuring identical timing and dependencies for daily refreshes.
Data Validation: Implemented robust, multi-layered data validation routines within Databricks and Delta Lake to ensure accuracy, completeness, and referential integrity across every migration stage.

Impact

The successful migration delivered:

A fully cloud-native data warehouse with elastic scaling and dramatically improved query performance.
Reduced infrastructure costs and eliminated on-prem maintenance overhead.
A modern data architecture ready for advanced analytics, AI integration, and future automation.
Improved data reliability and transparency, empowering business units with faster insights and confidence in their data.

Technologies Used

AWS
Databricks
Snowflake
Oracle
Delta Lake

15 years of healthcare domain experience combined with extensive technical skills.

We enable customers to exchange and use data across different systems while enforcing strong data governance principles to ensure data integrity and meaning.

Case Studies