A leading global biopharmaceutical services organization was facing increasing complexity in managing clinical and operational data across its worldwide research ecosystem.
With more than a hundred disconnected data sources, legacy SQL-based workflows and growing pressure to improve data quality, governance and operational efficiency, the client needed a modern platform capable of supporting advanced analytics and future AI initiatives.
The challenge extended beyond technology modernization. The client required a trusted enterprise data foundation that could unify clinical and operational data, automate reconciliation processes and improve confidence in business-critical information.
That’s where Persistent’s iAURA-powered DataOps transformation delivered measurable business impact.
When Data Fragmentation Slows Innovation
Given the high volume and complexity of enterprise data, the client’s existing data landscape struggled to keep pace. Data teams often relied on legacy SQL-based workflows to support reporting and reconciliation activities, resulting in increased manual effort and limited scalability. This led to several challenges that began to impact the organization’s ability to leverage data effectively:
- More than 125 disparate data sources creating silos across the enterprise
- Reporting inconsistencies and delays caused by disconnected systems
- Legacy SQL-based workflows limiting scalability and agility
- Limited observability across data pipelines and operational processes
- Lack of trusted reconciliation capabilities across critical datasets
- Increasing compliance, governance and auditability requirements
- Growing demand for advanced analytics and AI-driven insights
Without a unified approach to data operations, the organization risked slowing innovation while reducing confidence in the information being used to drive critical business decisions.
How Persistent Modernized Enterprise Data Operations with iAURA
Rather than continuing to manage disconnected systems and manual processes, the client chose to establish a modern enterprise data platform capable of supporting current operational requirements while creating a foundation for future innovation. This strategic shift focused on three priorities:
- Establishing a single, trusted source of enterprise data
- Automating reconciliation and data quality processes
- Improving governance, visibility and operational efficiency across the data ecosystem
Persistent partnered with the client to redesign its data ecosystem using iAURA DataOps on Azure Databricks, creating a unified enterprise-grade data platform for clinical and operational data.
Building a Trusted Enterprise Data Foundation
Persistent designed and implemented a cloud-native enterprise data platform capable of integrating clinical and operational data across the organization’s global ecosystem. Built using a Bronze, Silver and Gold medallion architecture, the platform provided a scalable framework for processing, governing and delivering trusted data across the enterprise.
The solution incorporated:
- Enterprise-grade data quality controls
- Automated error handling and reprocessing
- Centralized governance and reconciliation processes
- Secure and scalable cloud-native infrastructure
Unifying Clinical and Operational Data
The platform integrated operational and clinical data from CTMS, eTMF, ODM, Anaplan, IRMS, IVRS, FSP platforms, SDTM, Veeva and SAS environments.
By bringing these systems together, the organization gained greater visibility into enterprise operations and established a single source of truth that could support both operational decision-making and advanced analytics initiatives.
Automating Reconciliation Through AI-Powered DataOps
Persistent extended the platform with AI-powered DataOps capabilities that automated many of the traditionally manual tasks associated with data management and reconciliation.
This AI-powered solution enabled:
- Automated data profiling
- Intelligent reconciliation workflows
- Automated anomaly detection
- Continuous monitoring of data pipelines
- Improved operational observability
AI-driven agents were also deployed to monitor data pipelines and proactively identify issues before they impacted business operations.
Delivering Trusted Data at Scale
The transformation delivered significant improvements in operational efficiency, data quality, and enterprise data trust.
- More than 98% reconciliation accuracy achieved
- More than 90% automated anomaly detection
- Reduced manual validation efforts across data operations
- Improved stakeholder confidence in enterprise data
- Approximately 30% operational cost savings
- Faster SLA resolution and improved operational responsiveness
- Enhanced governance, traceability and collaboration across teams
- Established a trusted enterprise-grade data lake on Azure Databricks
From Data Silos to Trusted Enterprise Intelligence
By replacing fragmented systems and manual reconciliation processes with a unified, AI-powered DataOps platform, the organization established a trusted data foundation capable of supporting future growth and innovation. Today, the organization operates on a modern data platform that provides trusted, governed and scalable access to critical clinical and operational information.
What once required extensive manual reconciliation and fragmented processes is now automated through intelligent DataOps capabilities.
Persistent’s iAURA transformed data trust, operational efficiency and enterprise readiness for the next generation of life sciences innovation.
