Case Studies
How to read this work.
Each case study is framed around the delivery constraint, what changed because of the work, and why it matters. Start with the problem closest to what you are dealing with, then scan the relevant examples.
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Performance
Performance tuning
Dashboards too slow for daily use, or datasets that do not scale.
2 case studies
BrowseGovernance
Data quality and governance visibility
Data quality invisible to stakeholders, or governance without shared evidence.
1 case study
BrowseModernization
Reporting modernization
Legacy reports to migrate, reporting architecture to establish, or dashboards to rebuild.
3 case studies
BrowseSemantic model engineering
Semantic model engineering and validation
Models that need source control, validation, or structured review before deployment.
1 case study
BrowseAI-assisted BI
AI-assisted BI workflows
AI interest that needs honest scoping, a POC, or review-controlled guardrails.
2 case studies
BrowsePerformance
Performance tuning
Dashboards too slow for daily use, or datasets that do not scale.
Performance Tuning
Enterprise Data Platform Modernization
My role
Reporting-layer redesign, performance testing, and stakeholder communication
Constraint
Monolithic reporting structures plus a 30-user concurrency requirement for broader rollout
What changed
One analytics path reduced from 25M to under 100K rows; identified issues dropped from 43 to 2
Why this matters
Architecture-level performance work with rollout-readiness evidence, not just dashboard polish
Performance Tuning
Retail Dashboard Performance Tuning
My role
Dataset redesign and SQL optimization
Constraint
90-second dashboard load time across five departments
What changed
Load time dropped to 7 seconds through dataset and SQL logic changes
Why this matters
Measurable performance proof tied to daily operational use
Governance
Data quality and governance visibility
Data quality invisible to stakeholders, or governance without shared evidence.
Modernization
Reporting modernization
Legacy reports to migrate, reporting architecture to establish, or dashboards to rebuild.
Reporting Modernization
Trading Analytics and Compliance Reporting
My role
Senior Power BI development across report design, modeling, DAX, and testing
Constraint
Multi-party CTRM rollout with complex data dependencies and near-real-time reporting expectations
What changed
A new CTRM platform gained a validated reporting layer for middle-office and finance users across exception, compliance, and P&L monitoring
Why this matters
Shows specialist reporting delivery in a complex multi-party environment, including data-validation discipline and stakeholder sign-off
Dashboard Design
Customer 360 Lead-Generation Dashboard
My role
Dashboard design, prototyping, and stakeholder walkthroughs
Constraint
Fragmented customer, product, and insurance data across systems
What changed
A cross-sell workflow moved from fragmented analysis to a single drillable customer 360 dashboard
Why this matters
Shows end-to-end dashboard design, data modeling, and adoption-focused iteration rather than a static build
Reporting Modernization
Reporting Modernization: Cognos to Power BI Paginated Reports
My role
End-to-end migration delivery with multinational stakeholders
Constraint
10+ legacy Cognos reports with fragile maintenance model
What changed
Reports migrated to Power BI Paginated Reports with improved maintainability
Why this matters
Enterprise-scale migration, not a one-off conversion
Semantic model engineering
Semantic model engineering and validation
Models that need source control, validation, or structured review before deployment.
AI-assisted BI
AI-assisted BI workflows
AI interest that needs honest scoping, a POC, or review-controlled guardrails.
AI-Assisted BI
Gen-AI Debt Collection POC
My role
Azure OpenAI POC development
Constraint
Manual, non-personalized messaging approach
What changed
Demonstrated feasibility of AI-assisted personalized messaging
Why this matters
Scoped clearly as a POC, not a scaled transformation
AI-Assisted BI
AI-Assisted Control Tower Dashboard POC
My role
Visualization development, stakeholder validation, and POC documentation
Constraint
Multiple data domains and AI outputs had to be made usable for non-technical executives
What changed
A fragmented KPI view became a unified control-tower POC with AI-assisted anomaly visibility and handover materials
Why this matters
Shows AI-assisted BI delivered as a documented, stakeholder-validated POC rather than hype