Fortune 500 Financial Services Firm
Transforming Fortune 500 firm's legacy data warehouse to Snowflake on AWS
A Fortune 500 financial services firm's on-premises data warehouse was underperforming at a scale affecting operations, and the team recognized the migration as an opportunity to address years of accumulated data governance debt. CG Infinity led the migration to Snowflake on AWS using dbt, implementing Data Catalog, Lineage, Quality, Stewardship, and Reference Data Management disciplines alongside the technical work. Modern Agile and DevOps practices were adopted by client delivery teams throughout the engagement.
AT A GLANCE
A Fortune 500 financial services firm modernized an underperforming on-premises data warehouse to Snowflake on AWS using dbt as the cloud-native pipeline tool. The engagement paired the technical migration with implementation of Data Catalog, Lineage, and Data Quality disciplines and adoption of Agile and DevOps practices.
TOOLS
Snowflake | dbt | AWS
Service Line
Data & AI | AWS
The Challenge
On-premises warehouse limiting scalability and data governance
The client's on-premises data warehouse was underperforming at a scale affecting the business unit's ability to operate effectively. Beyond the platform itself, the team recognized the move to new technology as an opportunity to address data governance and quality debt that had accumulated over years. Executing a multiyear modernization of this scope required a partner able to manage both the technology migration and the operating model change simultaneously.
THE SOLUTION
Snowflake and dbt migration with modern data management practices
CG Infinity led the migration of analytics data to Snowflake on AWS using dbt as the cloud-native pipeline tool. Modern Agile Delivery, DevOps, and Quality Engineering practices were implemented and adopted by the client's teams throughout the engagement. Data Catalog and Lineage, Data Quality, Data Stewardship, and Reference Data Management disciplines were built into the delivery process as initial data subject areas went live on the new stack.
THE RESULTS
Legacy data warehouse modernized on Snowflake and AWS
The client gained greater operational agility, improved data quality, and a delivery model built to sustain the modernization over the long term, with Agile and DevOps practices adopted across delivery teams and data governance disciplines embedded in the process.
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