Accelerating Data Modernization in Life Sciences with Azure

From siloed SQL servers to a scalable Azure platform, Hylaine delivered a structured migration that unlocked data accessibility and analytics readiness.

Client Overview

A leading life sciences organization managing high volumes of partner data across multiple environments. With increasing demands for data availability, reporting agility, and system reliability, this client needed a cloud-forward solution that could keep pace with growth while aligning with stringent compliance requirements.

The Challenge

The client’s existing architecture relied on a patchwork of collocated SQL Server machines that lacked structure, scalability, and unified governance. Data integration workflows were fragmented, and the current ETL environment was no longer fit for purpose. Leadership sought a trusted technology partner who could not only migrate data to Azure but also provide a strategic roadmap for long-term modernization.

The Solution

Hylaine led a structured, phased transformation to design and implement an Azure-based data architecture that was scalable, governable, and aligned to the client’s broader modernization goals.

Key steps included:

Phase Zero: Discovery & Assessment

  • Conducted interviews with application owners and leadership
  • Mapped integration points, dependencies, and current data movement
  • Assessed infrastructure and provided recommendations

Phase One: Data Architecture & Storage Framework

  • Designed orchestration and migration workflows
  • Established scalable data storage patterns in Azure

Phase Two: Data Replication

  • Replicated structured data to Azure for continuity and testing

Phase Three: Virtual Machine Migration

  • Migrated key application VMs and executed consolidation testing

Phases Four to Six: Go-Live & Support

  • Completed UAT, full go-live, and provided support and knowledge transfer to internal teams

Throughout, Hylaine introduced enhancements to the MS SQL environment and ETL pipelines to improve data structure quality and standardize key objects.

Impact & Results

  • Successful migration from fragmented SQL infrastructure to a fully managed Azure SQL environment
  • Standardized data architecture and improved ETL workflows
  • Established a repeatable framework for future application migrations
  • Enabled long-term analytics readiness and data consolidation
  • Reduced system risk by aligning with modern cloud-native patterns

CEO Viewpoint

“This was about building trust through structure. We didn’t just migrate data—we gave the client a clear path forward that they could build on without us.”
— Adam Boitnott, CEO

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