bucky-ops/un-sdg-east-africa-insights-pipeline

Moduled, governance-first, open-source SDG monitoring analytics pipeline for East Africa; supports ingestion, cleaning, explainable ML, and policy-ready outputs for UN agencies, governments, and NGOs # UN SDG East Africa Insights Pipeline A modular, governance-first, open-source SDG monitoring analytics pipeline for East Africa, designed for UN agencies, governments, and NGOs. This project emphasizes transparency, interpretability, sustainability, and explainability in data analytics for policy-making. ## Overview - **Governance & Configuration**: Single source of truth for countries, SDGs, indicators, years, and data quality flags. - **Data Ingestion**: Immutable raw data storage with provenance logging. - **Cleaning & Standardization**: Pandas-based harmonization, missing value handling, and time alignment. - **Feature Engineering**: Human-understandable features like YoY change, rolling averages, and risk flags. - **Baseline ML Models**: Explainable regression and classification (Linear and Logistic Regression). - **Validation & Trust**: Simple bias checks, confidence scoring, and ethical cautions. - **Insights & Reporting**: Policy-ready summaries, charts, and text-based reports. - **Visualization Hooks**: Exports ready for Power BI, Tableau, GIS, and static PDFs. - **Deployment & Sustainability**: Documentation, maintenance guides, and capacity-building notes for East African institutions. ## Key Features - **Open-Source & No Cloud Lock-In**: Runs locally or on-premises. - **Ethical & Transparent**: All transformations are auditable; models are explainable. - **Policy-Focused**: Outputs designed for decision-makers (analyst-ready, policymaker-ready, UN-report-ready). - **Scalable & Maintainable**: Modular architecture survives staff turnover. - **Data-Driven Governance**: Provenance logs and quality flags prevent misuse. ## Getting Started 1. **Clone the Repository** ```bash git clone github.com cd un-sdg-east-africa-insights-pipeline ``` 2. **Install Dependencies** ```bash python -m pip install --upgrade pip python -m pip install pandas numpy scikit-learn joblib ``` 3. **Run the End-to-End Pi …