How MDS unified a century-old insurer’s fragmented data estate onto a single governed Azure Databricks platform in six months — built for AI from day one.
Customer: A U.S.-based property and casualty insurance company, founded in 1914 Industry: Property & Casualty Insurance Focus: Affinity insurance for educators, firefighters, law enforcement, and nurses Engagement: Azure Databricks — Unified Data Platform Timeline: 6 months, kickoff to production-ready Microsoft Funding: $25,000 Data Platform POC + Envisioning + AI Accelerator + Azure Accelerate Co-Sell Status: Registered Microsoft Co-Sell
The Customer
This insurer has been protecting the people who protect their communities since 1914. For over a century, the company has delivered auto, home, renters, and umbrella insurance through affinity programs built specifically for educators, firefighters, law enforcement officers, and nurses — professionals who dedicate their lives to public service.
That mission requires a deep, reliable understanding of policyholder data. But by the time this insurer engaged MDS, its data landscape had become a strategic liability rather than a strategic asset.
The Challenge: A Century of Data, None of It Unified
Critical business data — including policy and billing information flowing through Guidewire, the company’s core insurance platform — was fragmented across four disconnected environments: on-premises SQL Server databases, cloud-hosted SQL Server instances, AWS S3 storage, and SAP systems. Every analytics workflow required bridging the gap between cloud and on-premises infrastructure, creating layers of friction, manual effort, and operational complexity that slowed decisions and blocked innovation.
The operational consequences were real. Reporting was delayed. Analytical cycles were manual and time-consuming. And perhaps most significantly, the company could not begin moving toward the AI-driven analytics capabilities the business needed to remain competitive in a rapidly evolving insurance market.
The company’s Director of IT Infrastructure described it directly:
“Our biggest data challenge was the data architecture we had — being on-prem with cloud services wrapped around that. Beyond that, it was enabling us to make better exposures to AI — things you can’t do on-prem.”
The challenges were structural:
- Multi-source complexity: ~5 TB of insurance data lived across four disconnected source systems with no unified governance or analytics layer.
- Hybrid architecture evolution: Core Guidewire Claims, Policy, and Billing data required complex cloud-to-on-premises movement for every analytics workflow.
- AI readiness imperative: Without a cloud-native data foundation, there was no path to claims analytics, underwriting intelligence, or operational automation — regardless of how much the business wanted to get there.
- Compliance leadership: As a regulated insurer managing multi-segment policyholder PII across a distributed environment, the company needed to enforce data security consistently across a unified, governed platform.
As the Director of IT Infrastructure put it: “A significant amount of effort was spent integrating disparate systems and overcoming architectural limitations rather than focusing on innovation and business value.” The decision to fix the problem at the architectural level, not the workflow level, reflected the kind of strategic thinking that separates leaders from followers in the insurance industry.
The company needed more than a technology upgrade. It needed a trusted partner to architect the foundation that would carry it from legacy fragmentation to an AI-powered enterprise — and it needed that partner to bring the funding, expertise, and strategic vision to make it happen at speed. They chose MDS.
The Solution: Building the Foundation for Everything That Comes Next
Leveraging Microsoft’s $25,000 Data Platform POC funding, MDS designed and delivered a production-ready Azure Databricks environment on Microsoft Azure — the unified, governed, and scalable data platform the company needed, not just for its reporting requirements, but for the AI agents and advanced analytics workloads already planned for the future.
MDS structured the engagement into three deliberate phases, each aligned to the Azure Well-Architected Framework and Microsoft Cloud Adoption Framework:
Phase 1 — Discovery. MDS conducted stakeholder interviews and technical workshops with the customer’s team, reviewed existing architecture documentation, identified compliance and regulatory constraints specific to the insurance environment, and defined clear success criteria, KPIs, and a platform readiness checklist. The engagement was outcome-driven from day one.
Phase 2 — Plan. MDS designed the future-state architecture in full, evaluating and recommending Azure security, monitoring, and networking services tailored specifically to the company’s regulated operating environment. Stakeholder approvals were secured before a single line of infrastructure was provisioned.
Phase 3 — Build. The build phase delivered the complete, end-to-end implementation:
- Azure Landing Zone creation, fully aligned to Microsoft Cloud Adoption Framework best practices
- Databricks workspace provisioning and configuration — the core analytics engine
- Microsoft Entra ID integration for enterprise identity, access control, and data governance
- Azure Data Factory pipelines connecting SQL Server (on-premises and cloud), AWS S3, and SAP — unifying all four source systems into a single platform for the first time
- PII and data security compliance configuration enforced across the unified platform
- Environment validation, architecture documentation, and a formal knowledge transfer session enabling the customer’s internal team to independently manage and operate the platform
The engagement concluded with two weeks of post-build remediation support, ensuring a smooth transition to production operations. The entire engagement was delivered in six months from kickoff to production-ready deployment.
Microsoft Technologies Deployed
| Technology | Role |
| Azure Databricks | Unified data platform and core analytics engine |
| Microsoft Entra ID | Enterprise identity, access control & governance |
| Azure Data Factory | Multi-source data connectivity & integration |
| Azure SQL | Cloud database layer |
| Azure Landing Zone | Secure, governed cloud foundation aligned to CAF |
The Technical Challenges MDS Solved
This was not a textbook deployment. MDS’s engineering team — led by Moises Salum (Senior Data Engineer) and Kareem Bennett (Sr. Azure Architect) — encountered and resolved real-world production challenges that required genuine depth of expertise:
- S3 connection instability caused by the sheer volume of data at ~5 TB scale required architecture-level design adjustments that went beyond standard configuration.
- Azure Data Factory pipeline throttling caused by high file volumes was resolved through targeted pipeline optimization and configuration tuning.
- Live SQL Server integration as a real-time source of truth for analytical model ingestion required custom connectivity design across a complex hybrid environment.
- Databricks cluster right-sizing balanced processing performance with sustainable, long-term cost efficiency across ongoing workloads.
Microsoft Co-Investment: Funding the Transformation
A defining characteristic of this engagement — and a key differentiator for MDS — was the depth and breadth of Microsoft co-investment secured on the customer’s behalf. MDS identified, qualified, and stacked four distinct Microsoft funding programs simultaneously:
✅ $25,000 Microsoft Data Platform POC Funding — reducing customer risk and accelerating time-to-value for Phase 1
✅ Microsoft Envisioning Funding — defining the customer’s enterprise AI transformation roadmap
✅ Copilot/AI Agents Accelerator Funding — funding Phase 3 enterprise AI agent deployment via Copilot Studio and Microsoft Foundry
✅ Azure Accelerate: Data Platform Assess + POV L — securing the funding runway for Phase 2 analytics expansion
✅ Registered Microsoft Co-Sell — Microsoft field team aligned, invested, and engaged throughout the engagement
Few partners in the Microsoft ecosystem can execute this level of funding orchestration across multiple programs simultaneously. The result was a transformation that moved materially faster and at materially lower risk than it could have without this depth of partnership.
The Results: Simplified, Unified, and AI-Ready
The impact of the engagement was immediate and foundational. For the first time in the organization’s 110-year history, its insurance data — all ~5 TB spanning Guidewire, SQL Server, AWS S3, and SAP — exists on a single, unified, governed Microsoft Azure platform. The hybrid complexity that had defined every analytics workflow is gone. Guidewire policy and billing data now moves cloud-to-cloud, eliminating the architectural friction that slowed decision-making and blocked analytical progress. PII and data security compliance requirements — non-negotiable for a regulated insurance carrier — are formally addressed and enforced across the entire unified platform. The governance infrastructure is in place. The security posture is production-grade.
In the Director of IT Infrastructure’s words:
“It’s simplified it. Now it’s moving from cloud to cloud — that makes it much more simplistic to build. More simplified structure at the end of the day.”
“By transitioning to cloud-to-cloud integrations, we have streamlined our architecture, increased scalability, and accelerated our ability to develop and deploy new capabilities.”
On the MDS relationship:
“We’ve done a lot of things with MDS, and you guys have always done a great job for us. Always responsive, always professional, always get stuff done.”
“Throughout our partnership, MDS has consistently provided outstanding service and execution. Their responsiveness, professionalism, and commitment to delivering results have contributed significantly to the success of our initiatives. Simply stated, they get stuff done!”
The Road Ahead: From Data Foundation to AI-Powered Enterprise
What MDS delivered is not the end of the journey — it is the beginning. Phase 1, the Azure Databricks foundation, was architected from day one with Phase 3 in mind. Every architectural decision was made to ensure the platform can support Copilot Studio agents and Microsoft Foundry workloads without re-architecture, protecting the customer’s investment at every stage of the roadmap.
| Phase | Engagement | Status |
| Phase 1 | Azure Databricks — Unified Data Foundation | ✅ Delivered |
| Phase 2 | Azure Accelerate: Data Platform Assess + POV L — Expanded Analytics | 🔄 Scoping |
| Phase 3 | Copilot Studio + Microsoft Foundry — Enterprise AI Agent Deployment | 🔵 Funded & Planned |
Building toward AI on this foundation is a confirmed strategic priority for the organization. The platform is ready. The funding is secured. The roadmap is clear.
Why MDS
Three capabilities set MDS apart:
Microsoft Funding Mastery. MDS didn’t just deliver a project — it secured the financial infrastructure to make a multi-year transformation possible. By stacking four Microsoft funding programs, MDS reduced the customer’s investment exposure while maximizing the scope, speed, and ambition of the engagement.
Specialist Delivery Depth. The work was executed by specialists who solved production-grade challenges across four heterogeneous source systems. The result was a platform built to enterprise standards, not a proof-of-concept.
Strategic Vision Beyond the SOW. MDS saw further than the Statement of Work. The architecture delivered in Phase 1 was designed for the AI agents coming in Phase 3. That forward-looking vision — and the funded roadmap to prove it — is the difference between a vendor and a strategic partner.
Scalability
The MDS Azure Databricks framework is a methodology built for regulated industries, where data governance, compliance, and scalable analytics are non-negotiable. The Azure Landing Zone architecture, Entra ID integration pattern, and multi-source connectivity model (SQL Server + S3 + SAP) are directly transferable to any insurance carrier, regional bank, or regulated enterprise facing the same data modernization opportunity.
Maureen Data Systems (MDS) is a Microsoft partner specializing in cloud modernization, data platform transformation, AI adoption, and security solutions for enterprise and regulated-industry customers. MDS combines deep Microsoft technical expertise with a proven ability to navigate the Microsoft funding ecosystem, delivering transformations that are faster, lower-risk, and purpose-built for what comes next. Learn more at www.mdsny.com.