How I Identified Key Problems and
Expanded Business Strategy into a New Venture
2024 - 2025
Mapping Enforcement of Lead Hazard Orders in Milwaukee
Data Analysis and Spatial Visualization
by ArcGIS Pro 3
Goal
Map parcels with identified lead hazards in Milwaukee and analyze enforcement delays to reveal systemic gaps in addressing child lead exposure.
Motivation
A personal project inspired by a family member's work at the city's health department, I used public data to visualize lead hazard orders and enforcement delays for the public good.
Spatial Data Visualization Goals
Lead poisoning among children due to exposure from older houses is an endemic public health issue in Milwaukee. Delays in enforcement of the city's orders to fix these houses may exacerbate the health risks.
Mapping Hazardous Locations
Identify and map the locations of houses with lead hazards using Milwaukee Open Data records from the City of Milwaukee’s Land Management System.
Analyzing Enforcement Timelines
Evaluate the duration between the city's order for repairs and the subsequent court action (which is initiated if the owner fails to comply after three notices ). This timeline could be a key indicator of systemic delays that contribute to prolonged exposure.
Research Insights
Data Sources
Data Source 1
The orders for property owners are publicly available for download on the City of Milwaukee website
Data Source 2
Milwaukee Track Boundary Data from Milwaukee County GIS & Land Information
Data Source 3
Milwaukee Aerial Images from Milwaukee County GIS & Land Information
Data Source 4
Census Data from US Census Bureau: ACS Population and Housing Basics – Boundaries
Design Process
Processes
Step 1. Data Collection
Downloaded three datasets representing different types of enforcement orders to understand the scope and timeline of property violations.
Step 2. Data Understanding & Geocoding
Analyzed table structures, identified key columns (especially zip codes), and studied geocoding methods to prepare for mapping.
Step 3. Process & Timeline
Each order type has an expected timeline; ideally, if orders are not corrected, all three stages would take no more than 5 months. A 1-month buffer was added for a more realistic 6-month estimate.
Step 4. Case Selection
Filtered down to 73 houses that appeared in all three datasets—these likely experienced the most significant delays.
Step 5. Timeline Analysis
Created a timeline chart to visualize order progression, identify delays, and flag active cases exceeding six months.
Step 6. Mapping with ArcGIS Pro
Analyzed and visualized the data within geolocations and census data using ArcGIS Pro 3.
Reach New
Heights
Product Name
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Outcomes &
Key Findings
Outcomes
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Built a timeline visualization tool to help understand how long properties remain in violation.
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Mapped out risk clusters using ArcGIS Pro, supporting data-driven decisions for prioritization.
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Highlighted that 89% of cases exceed the ideal enforcement timeline, emphasizing the urgent need for intervention.
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Identified potential systemic issues related to property ownership (e.g., rental properties facing longer delays).
Key Findings
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Storytelling through data is critical—visuals like maps and timelines help turn complex datasets into actionable insights.
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Empathy can drive impact—designing with a real user (my family member) in mind helped ground the work in practical needs.
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Geospatial tools like ArcGIS are powerful for revealing patterns that spreadsheets alone can’t show.
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Clear definitions and filtering logic (like selecting houses with all 3 order types) are essential for focused, meaningful analysis.