Tier-1 European Bank — Deterministic Test Data Across Oracle, MongoDB & Kafka
A Case Study in Accelerating Test Data Delivery for Analytics & API Teams
In global finance, speed is survival. A top European bank was stalled by a fragile, four-week manual test-data process—“dependency hell” that derailed rollouts and raised competitive and regulatory risk. Deploying DATAMIMIC shifted them from risky masking to on-demand, compliant synthetic data, decoupling teams, enabling self-service, and cutting the test-data lifecycle by 90%. The result: parallel development restored and a chronic bottleneck turned into a strategic edge.
Customer
Tier-1 European Bank
Industry
Financial Services
Techstack
DATAMIMIC Toolbox, Oracle, MongoDB, Kafka, Tosca DI, CI/CD
Service
Proof of Value, Enablement, Integration & Automation
Challenge
The bank’s Analytics and API departments were repeatedly blocked by their test-data process. Every refresh required masked snapshots that took 20–28 days to prepare, involved 5–6 engineers, and often broke JSON joins across Oracle schemas, MongoDB collections, and Kafka event payloads.
Schema changes triggered constant rework, QA was left waiting on data engineers, and several high-profile digital rollouts were delayed due to missing or inconsistent data. The hardest challenge: building deterministic JSON structures across heterogeneous data sources without manual patching.
Solution
We started with a Proof of Value to show that DATAMIMIC could assemble JSON test data deterministically from multiple systems. Once successful, the engagement continued with enablement and feature co-design, ensuring the client’s teams could extend rulesets themselves.
Ruleset-driven synthesis
JSON documents generated from Oracle, MongoDB, and Kafka according to specifications.
Deterministic consistency
The same rules produced identical entities across systems, preserving integrity automatically.
Enablement
Hands-on guidance to teach teams how to model and use DATAMIMIC correctly.
Automation
Full integration into Tosca DI and CI/CD pipelines created a zero-touch data flow.
By moving from masked snapshots to deterministic rulesets, our teams gained independence. Test data became a resource we generate on demand, not a bottleneck we wait weeks for.
from Tier-1 Bank
Result
Within weeks, the bank transformed its delivery capability, achieving a powerful combination of speed, quality, and compliance
Massive Efficiency Gains:
Lead Time Reduction
Massive reduction in test data preparation time
Engineer Hours Saved
Significant resource optimization achieved
Parallel Execution
Cross-team now runs in parallel, free of dependencies.
Improved Quality & Confidence:
- Data consistency: JSON entities were aligned across Oracle, MongoDB, and Kafka automatically, without manual fixes.
- Support tickets: End-to-end automation cut support tickets from 3–5 per cycle to just 1–2.
Bulletproof Compliance & Risk Mitigation:
PII exposure: Pre-production environments reduced live PII from ~100% to ≤5% residual, on track to zero with ongoing policy enforcement.