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Geopolitical Risk Engine: Predicting Global Conflict Trends Using ETL Pipelines and Machine Learning

A complete data engineering project that processes global conflict historical data via ETL pipelines, uses Poisson regression models to predict the conflict frequencies of various countries from 2025 to 2026, and integrates Power BI for interactive visual analysis.

地缘政治数据工程ETL机器学习泊松回归Power BISQL Server风险分析数据可视化预测建模
Published 2026-06-06 08:15Recent activity 2026-06-06 08:19Estimated read 1 min
Geopolitical Risk Engine: Predicting Global Conflict Trends Using ETL Pipelines and Machine Learning
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Section 01

导读 / 主楼：Geopolitical Risk Engine: Predicting Global Conflict Trends Using ETL Pipelines and Machine Learning

Introduction / Main Floor: Geopolitical Risk Engine: Predicting Global Conflict Trends Using ETL Pipelines and Machine Learning

A complete data engineering project that processes global conflict historical data via ETL pipelines, uses Poisson regression models to predict the conflict frequencies of various countries from 2025 to 2026, and integrates Power BI for interactive visual analysis.

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