Data Lake / Data Warehouse Modernization
A major Canadian bank needed to unify fragmented capital-markets data spread across dozens of applications and domains so teams could stop duplicating information and start producing trusted analytics and AI-driven insights faster.
Reported impact
The bank modernized its capital-markets data foundation, accelerated integration of new data sources, reduced duplication, and created a resilient platform for analytics and AI initiatives that can move new ideas to market faster.
The capital-markets division of a major Canadian bank built a unified data hub on MongoDB Enterprise Advanced and MongoDB Atlas to replace siloed data stores spread across 76 applications and 113 data domains. The new architecture uses MongoDB’s flexible document model as the core of a data-mesh strategy so domain teams can own and publish data products while reducing duplication and governance drift. The bank consolidated client, market, transaction, and risk data into one hub, then integrated Databricks for machine learning, visualization, and other analytics workloads. MongoDB’s querying, indexing, replication, and multiregional failover support dashboards, recommender systems, and resilient disaster recovery, while Atlas security features such as SSO SAML and encryption helped satisfy enterprise compliance requirements. By treating MongoDB as the shared operational core, the bank created a faster route to trusted analytics across capital markets.
Client, market, transaction, and risk data from dozens of applications are consolidated into a MongoDB-based data hub, queried and indexed for domain teams, then extended into Databricks and BI tooling for dashboards, machine learning, chatbots, and recommender workflows.
“By extending the data hub to other frameworks, we’ve built strategic dashboards using business intelligence tools.”
“MongoDB Atlas checked all the boxes and would let us adopt features like SSO SAML integration, encryption, and different support tiers that fit the criticality of our use cases.”
“MongoDB has proven to be production ready, resilient, adaptable, scalable, and widely used.”
“We needed to implement a central, flexible, scalable, and resilient home for capital markets data.”
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