Project Summary
A government-affiliated not-for-profit organization faced growing operational complexity due to fragmented data systems and a lack of centralized oversight. To support long-term service delivery and compliance mandates, they partnered with GOBI Technologies to develop a scalable data strategy and implement foundational governance practices. The result was improved data quality, enhanced visibility, and a future-proof environment for analytics and automation.
Challenges
As a regulatory organization operating across a large provincial scope, the agency managed growing volumes of data from disparate systems used for customer management, dispute resolution, education, and compliance tracking. Over time, several issues emerged:
- Siloed Systems and Inconsistent Data Models: Existing tools lacked integration, preventing cross-functional analysis and full data visibility.
- Low Data Trust and Gaps: Inaccurate, incomplete, or duplicated records created delays and undermined decision-making.
- No Formal Governance: Data ownership, policies, and quality standards were undefined, creating risk for compliance and operational accountability.
- Reporting Bottlenecks: Legacy tools required manual data prep and limited the organization’s ability to scale analytics or reporting across departments.
The organization needed a clear strategy to unify its data ecosystem and lay the foundation for modern business intelligence.
Approach and Solution
GOBI Technologies delivered a phased engagement to define, align, and operationalize a data governance and reporting strategy:
1. Data Discovery and Strategy Design
Through stakeholder workshops, we identified key data sources, business processes, and reporting pain points. This formed the basis of a strategic roadmap focused on:
- Prioritizing trusted data domains
- Establishing shared definitions and ownership
- Aligning reporting goals with departmental mandates
2. Foundational Data Governance Implementation
We deployed a proof-of-concept using Microsoft Purview to demonstrate metadata management, data cataloging, and policy definition across environments. This included:
- Defining key domains and data stewards
- Creating reusable policies for classification, access, and retention
- Improving visibility into the data landscape through lineage and classification features
3. Future-Ready Architecture Planning
Instead of rushing into implementation, we designed an extensible model for integrating additional data sources and supporting future analytics and AI workloads. Our architecture design accounted for:
- Scalability across departments and platforms
- Support for structured and unstructured data
- Cloud-native flexibility and hybrid environment compatibility
4. Organizational Enablement
We delivered stakeholder training and governance playbooks to help the client sustain and scale the program internally. This included:
- Data steward onboarding
- A reporting standards guide
- Change management support for end users and leadership
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Conclusion
By building a unified data governance framework, the organization established a trusted, well-documented environment to support its expanding data needs:
- Clarity and Control: Improved data accuracy and eliminated confusion through centralized metadata and defined ownership.
- Governance Foundation: Microsoft Purview POC demonstrated scalable compliance, lineage tracking, and policy enforcement.
- Faster Insights: Standardized reporting workflows and data models reduced delays and improved reporting quality.
- Future-Ready: With a governance-first strategy in place, the client is now equipped to scale analytics and automation confidently.
