CRISP-DM in Public Programme Delivery Pipelines
How I adapt CRISP-DM phases to match institutional timelines and stakeholder decision windows.
Read noteInsights Blog
This blog documents the practical side of my work, how models are scoped, validated, communicated, and translated into implementation-ready decisions across analytics, health, and program contexts.
Each note is intentionally concise and execution-focused: method choices, tradeoffs, quality controls, and what actually works when data projects move from theory into operational use.
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Choosing Between Descriptive and Predictive Workflows
Decision criteria for selecting fit-for-purpose analysis depth under real operational constraints.
Read noteData Quality Checks Before Dashboard Delivery
A practical checklist for auditability, validation, and source consistency before publishing dashboards.
Read notePrompt Governance for AI-Assisted Analytics Teams
Prompt standards and review controls that maintain quality when teams adopt generative AI tools.
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