When your database handles the load but blocks your decisions
Before
to manage growth: teams operate without data
After
saved on back-office processing
saved on back-office processing
extraction of operational data
BI opened up to non-IT teams
Blank, the Crédit Agricole group neobank dedicated to freelancers, offers a fully digital service: a business bank account, automated VAT, management of URSSAF social contributions. Growth is there, but the back-office and product teams are working without visibility. The DynamoDB architecture, designed for low-latency operational scalability, exposes no native analytics surface. The result: zero reliable dashboards, time-consuming manual exports, and decisions made on intuition.
THE STORY
OUR APPROACH
4 steps to get there
Audit of the existing architecture
A complete analysis of the system: DynamoDB data model, access patterns, application data flows, code repository. The verdict is clear: the operational architecture is optimized for transactional performance, not for ad hoc analytical queries. Costly aggregations and table scans are out of reach without degrading production.
Identifying the target solution
Exploration of the extraction options: batch export, native Change Data Capture, replication. DynamoDB Streams stands out: it captures every change in real time without affecting the source table. Paired with Lambda for transformation and routing, it opens the way to a lightweight analytical data lake, separate from the operational plane.
Design and POC
End-to-end solution architecture: DynamoDB Streams → transformation Lambda → analytical storage → Metabase. The POC validates data consistency, extraction latency (near real time) and the Metabase user experience for non-technical users. Business teams can write their first SQL queries without IT support.
Industrialization and production rollout
From POC to production through Infrastructure as Code (CloudFormation). Every component (streams, Lambda functions, IAM permissions, analytical database) is declared, versioned and reproducible. Deployment assistance and knowledge transfer to the internal teams.
RESULTS
The measurable impact
Real-time extraction pipeline in production in 4 months. Back-office and product teams access their data on their own through Metabase, with no IT ticket and no manual export. 1 FTE saved on back-office processing, streamlined operational processes, and a decoupled analytics architecture that evolves independently of the transactional plane.
Your operational data deserves better than a weekly CSV export
Book a discovery callSIMILAR CASE STUDIES
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