Pharma: Validation of a Data Lake / Analytics Platform Used for Quality Trending
What we succeed?
As a result of the partnership we established with Validfor, full visibility, traceability, audit readiness and standardized workflows and centralized validation knowledge
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The Problem
Unvalidated Analytics Platform Driving Quality Decisions from Unverified Data Transformations
A centralized analytics platform aggregates deviations, OOS events, and batch data to drive quality trending decisions — but without validated data ingestion pipelines and transformation logic, reports cannot be trusted as accurate representations of the underlying data. Medium-high risk arises from analytics directly influencing quality decisions and the inherent risk of data transformation errors.
Medium-high risk: analytics outputs directly drive quality decisions
Data transformation risk — no validation that meaning or value is preserved through pipeline
No audit trail coverage for pipeline changes or report publishing
Reports not traceable to source datasets or transformation logic
The Strategy
Validated Data Pipelines with End-to-End Traceability, Access Control, and Audit Trails
The validation scope covered data ingestion pipelines, transformations, audit trails for data changes, access control, and report integrity — with testing focused on confirming that data mapping and transformations introduce no alteration of meaning or value from source to published report.
Validate data mapping and transformations; confirm no alteration of meaning or value across pipeline
Access control validation for pipeline modifications and report publishing workflows
Audit trail coverage for all pipeline changes and report publishing events
I’ve worked with many others and you’re way ahead of anything I’ve seen.
Pharma Manufacturing Client
The Solution
Trusted & Audit-Ready Analytics Platform for GxP Quality Trending
Every quality trending report is traceable back to its source datasets and transformation logic, with changes to pipelines and reports governed by documented controls. The validated platform ensures that analytics outputs are accurate, attributable, and inspection-ready — eliminating ambiguity in quality decision-making.
Reports fully traceable to source datasets and transformation logic
Pipeline and report changes controlled and reviewed before deployment
Audit trails verified for all data changes, pipeline modifications, and report publishing events
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