BigData2025-Rev/p3
Jan 2025 – Feb 2025
2 Months active
Languages Used
PythonPower BI
Technical Skills
Data CleaningData EngineeringData TransformationETLPySparkBusiness Intelligence
Jaystar2323
PROFILE
Jaystar2323
Kim Hilke developed and enhanced demographic data preparation and analytics features for the BigData2025-Rev/p3 repository over a two-month period. Using PySpark and Python, Kim engineered an integrated data cleaning pipeline that standardized column names, enriched geodata by decade, and consolidated cleaning steps to improve data quality and reduce downstream errors. The work included implementing majority and minority race trend analysis across 2000 and 2020 census data, exporting results to CSV, and creating Power BI-ready reporting assets. Kim also reorganized the project structure for maintainability, demonstrating depth in data engineering, transformation, and business intelligence workflows without introducing critical bugs.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
8Total
Bugs
0
Commits
8
Features
3
Lines of code
315
Activity Months2
Your Network
16 people
Work History
February 2025
5 Commits • 2 Features
Feb 1, 2025February 2025 performance summary — BigData2025-Rev/p3: Delivered key demographic analytics features and a reporting-ready structure, with no critical bugs reported. Business value includes a repeatable CSV-based output of race trends (2000 vs 2020) and a Power BI reporting asset for stakeholder dashboards. The month also included a project reorganization to improve maintainability and future scalability.
5 Commits • 2 Features
Feb 1, 2025February 2025 performance summary — BigData2025-Rev/p3: Delivered key demographic analytics features and a reporting-ready structure, with no critical bugs reported. Business value includes a repeatable CSV-based output of race trends (2000 vs 2020) and a Power BI reporting asset for stakeholder dashboards. The month also included a project reorganization to improve maintainability and future scalability.
February 2025
January 2025
3 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for BigData2025-Rev/p3: Delivered a major upgrade to the Enhanced Demographic DataCleaner for Data Preparation and Geodata Handling. Key changes include filtering by summary levels, integer casting for population columns, decade-based year/geodata enrichment, standardization of column names, integration of cleaning methods into the main script, and outputs prepared in CSV and ORC formats. Simplified geodata logic and introduced descriptors like id and urban_rural for final selection. This work was implemented through three commits that improved demographic analysis methods, cleaned up data methods and main integration, and standardized naming.
January 2025
3 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for BigData2025-Rev/p3: Delivered a major upgrade to the Enhanced Demographic DataCleaner for Data Preparation and Geodata Handling. Key changes include filtering by summary levels, integer casting for population columns, decade-based year/geodata enrichment, standardization of column names, integration of cleaning methods into the main script, and outputs prepared in CSV and ORC formats. Simplified geodata logic and introduced descriptors like id and urban_rural for final selection. This work was implemented through three commits that improved demographic analysis methods, cleaned up data methods and main integration, and standardized naming.
Activity
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Quality Metrics
Correctness87.6%
Maintainability87.6%
Architecture87.6%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Power BIPython
Technical Skills
Business IntelligenceData AnalysisData CleaningData EngineeringData TransformationData VisualizationETLPySpark
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