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Higher EducationData Governance & Engineering

Enterprise Data Governance Transformation

A complete overhaul of a world-renowned research university's legacy data governance infrastructure - modernizing decades-old systems, eliminating compliance exposure across three federal frameworks, and transforming how researchers access data.

Role on This Engagement

This was a large enterprise team engagement, with the data governance domain owned and delivered end-to-end by a single engineer - from legacy system audit through architecture design, implementation, and knowledge transfer.

3
Compliance Frameworks
PB+
Research Data Governed
6
Enterprise Technologies

Client Overview

Washington University in St. Louis

Washington University in St. Louis is a world-renowned private research university, consistently ranked among the top institutions globally. With multiple research centers generating petabytes of data annually, the university required a modern data governance framework to support their research mission while ensuring compliance with federal regulations including HIPAA, FERPA, and federal research data mandates.

The Challenge

Legacy Infrastructure

Decades-old data systems created silos across departments, making it nearly impossible for researchers to access and share data efficiently. Manual processes consumed significant staff time and introduced data quality issues.

Compliance Gaps

The existing infrastructure lacked proper data lineage tracking, access controls, and audit capabilities required for regulatory compliance. This put the university at risk during federal audits.

Researcher Bottlenecks

Data requests routed through data librarians and manual fulfillment workflows took several days to complete, blocking research progress and creating persistent backlogs across the institution.

Scalability Constraints

Growing research data volumes were overwhelming existing infrastructure, leading to performance degradation and increasing costs for temporary workarounds.

Approach

Most data governance engagements are treated as purely technical problems. This one wasn't. The outcome was exceptional because the work was grounded in equal parts technical depth, regulatory fluency, and human-centered design - three things most engineers bring one of, not all three.

Human-Centered Research

Before any architecture decisions were made, extensive user research was conducted across the institution - interviews with administrators, professors, researchers, and students. Pain points were mapped, workflows documented, and the real human cost of the existing system was fully understood before a single line was written.

Regulatory Fluency

A background spanning biomedical engineering, medical device development, regulatory technology, and public policy meant HIPAA, FERPA, and federal research data mandates were understood at a depth most engineers can't reach - not as compliance checkboxes, but in their real implications for workflows and institutional risk.

Technology Chosen for People

Apache NiFi, Azure Synapse, and Collibra were selected to make data access feel less like filing a request with a librarian and more like shopping on Amazon - browse, add to cart, check out. The technology served the human experience, not the other way around.

The Solution

Azure Synapse Analytics

Deployed a unified analytics platform combining big data and data warehousing capabilities, enabling researchers to query petabytes of data with sub-second response times while maintaining cost efficiency.

Apache NiFi Pipelines

Implemented robust, self-healing data pipelines with Apache NiFi for real-time data ingestion and transformation. Built-in data provenance tracking ensured complete visibility into data lineage.

Collibra Data Governance

Established an enterprise data catalog with Collibra, enabling automated data classification, policy enforcement, and compliance reporting across all three federal frameworks.

Governance Domain Ownership

Enterprise data governance isn't just technical - it requires navigating organizational complexity, managing stakeholder expectations, and driving adoption across departments with competing priorities.

Legacy System Overhaul

Completely replaced decades-old siloed systems with a modern governance layer built on Collibra, creating a single source of truth for all university data assets.

Compliance Architecture

Designed and implemented automated compliance enforcement across HIPAA, FERPA, and federal research data mandates - turning a manual audit risk into a continuously monitored control layer.

Stakeholder Alignment

Coordinated across IT, research departments, compliance, and university leadership, translating governance requirements into technical decisions that worked for every stakeholder group.

Technologies Used

Azure Synapse AnalyticsApache NiFiCollibraAzure Data FactoryPower BISQLJava

Value Delivered

Before

Data requests were routed through data librarians and manual fulfillment workflows, taking several days from submission to delivery - blocking research progress and creating persistent IT bottlenecks across the institution.

After

Minutes. Researchers access data directly through a self-service platform, with governance enforced automatically - no librarian queues, no IT tickets, no waiting.

Days → Minutes

Research data requests that previously required manual librarian fulfillment and multi-day turnaround now resolve in minutes through self-service access, removing the single biggest bottleneck in the research workflow.

Compliance Risk Eliminated

HIPAA, FERPA, and federal research data mandates enforced automatically through data lineage tracking, access controls, and audit trails built directly into the governance layer.

Infrastructure Built to Last

Decades-old siloed systems completely replaced with a modern, cloud-native governance framework designed to scale with growing research data volumes and evolving regulatory requirements.