Case study
Unified Data Fabric & Operational Intelligence Engine
Connected fragmented data silos into a unified data fabric, reducing data retrieval time by over 50% and eliminating intelligence gaps.
Overview
Large organizations often have data trapped in silos, causing slow decision-making and compliance risk due to fragmented records.
The Challenge
Getting a straight answer meant querying legacy SQL databases, Redis streams, and time-series logs separately, then manually reconciling what came back, with no single, trustworthy version of the truth.
The business impact:
- Decision-makers waited on manual data reconciliation before they could act on anything.
- Fragmented records made regulatory audits slower and riskier than they needed to be.
- The same data question could get a different answer depending on which system someone happened to query.
Approach
How do you query fragmented systems as if they were one?
Legacy SQL, Redis streams, and TimescaleDB logs each held part of the picture, with no shared query layer. We engineered a GraphQL-based middleware for federated query orchestration across all three, creating a single source of truth teams could query directly.
How do you keep that unified view fast and audit-ready?
A unified query layer is only useful if it's fast and defensible. We implemented an intelligent Redis caching strategy for performance, plus an append-only audit trail in TimescaleDB, giving the organization immutable data lineage for regulatory compliance.
Tech Stack
Outcome
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