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Data Science & Analytics ​

Overview ​

The Data Science & Analytics service processes aggregated case data to uncover patterns, trends, and KPIs.

Purpose ​

  • Support evidence-based decision-making.
  • Identify high-risk areas and populations.
  • Evaluate service performance.

How It Works ​

  1. Data Collection:
    • Aggregate structured data from case records.
  2. Analytics Engine:
    • Statistical summaries.
    • Predictive modelling for case volumes.
  3. Visualization:
    • Dashboards, charts, and geospatial heatmaps.
  4. Reporting:
    • Export in PDF, Excel, or interactive web formats.

Input ​

json
{
  "cases": [
    { "type": "Neglect", "location": "Kisumu", "date": "2025-06-01" },
    { "type": "Abuse", "location": "Nairobi", "date": "2025-06-03" }
  ]
}

Output ​

json
{
  "insights": {
    "total_cases": 2,
    "top_location": "Nairobi",
    "most_common_type": "Abuse"
  }
}

Dependencies ​

  • Pandas, NumPy for data processing
  • Matplotlib, Plotly for visualization
  • Geospatial libraries for mapping

Human Impact ​

  • Turns raw case data into clear, actionable intelligence.
  • Helps allocate resources where they’re needed most.

Pipeline End