Modern data architecture helps predict customer behavior

financial services client


evolv’s financial services client wanted to grow through acquisition, as well as an immediate need to modernize their data architecture by migrating more than 500 tables from their existing on-premises instances (across 12 unique data source) to a cloud-based data warehouse.

The legacy platform also was reaching capacity (in both storage and processing power), resulting in performance issues and ongoing interventions to “keep the lights on.”

The client also envisioned building an automated ingestion framework to load Snowflake with extensibility to onboard additional targets in the future state. They relied on evolv to help make the significant investment required to upgrade the current solution to support long-term business needs.


evolv led the team responsible for planning, managing and successfully executing the data migration.

  • Performed a detailed discovery to facilitate the creation of a comprehensive migration strategy and planning for the migration by following a “cloud-first” approach.
  • Worked closely with the client’s Engineering, Security, Architecture, Business Reporting and User Engagement teams throughout the program.
  • The team set and tracked progress on milestone achievements, client deliverables, and migration status to provide visibility to senior stakeholders.


  • Delivered a modern ingestion platform that was architecturally designed to support easy plugin of additional loading targets
  • Created a robust error-handling and event logging solution to give confidence and auditability in the data warehouse
  • Improved data accessibility, increasing the speed of analysis and actionable insights from dynamic market and customer trends
  • Equipped business leaders to predict customer behavior and drive better outcomes across web, call center and marketing channels