H6WU6R/DSA3101-Group-4
Mar 2025 – Apr 2025
2 Months active
Languages Used
PythonCSVMarkdown
Technical Skills
Data AnalysisData PreprocessingData ProcessingData VisualizationExploratory Data AnalysisFeature Engineering
hanmei-lee
PROFILE
Hanmei-lee
Over two months, this developer built a unified Campaign Performance Analysis and Customer Segmentation Platform in the H6WU6R/DSA3101-Group-4 repository, focusing on marketing analytics and data-driven decision support. They engineered an end-to-end analytics pipeline using Python, Pandas, and Scikit-learn, integrating data loading, preprocessing, feature engineering, PCA-based clustering, and visualization to enable actionable segmentation and campaign insights. Their work included modularizing the codebase for maintainability, implementing MMM-style analysis for budgeting optimization, and enhancing reporting capabilities. By integrating economic modeling and robust data pipelines, they established a scalable foundation for marketing analytics, supporting both campaign evaluation and strategic planning.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
13Total
Bugs
0
Commits
13
Features
4
Lines of code
8,343
Activity Months2
Your Network
74 people
Work History
April 2025
11 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for H6WU6R/DSA3101-Group-4: Delivered a set of high-impact analytics capabilities and foundational data assets, alongside targeted codebase cleanup to improve maintainability and clarity of responsibilities. Business value focused on enabling data-driven marketing optimization and better budgeting decisions through robust data pipelines and MMM-style analysis.
11 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for H6WU6R/DSA3101-Group-4: Delivered a set of high-impact analytics capabilities and foundational data assets, alongside targeted codebase cleanup to improve maintainability and clarity of responsibilities. Business value focused on enabling data-driven marketing optimization and better budgeting decisions through robust data pipelines and MMM-style analysis.
April 2025
March 2025
2 Commits • 1 Features
Mar 1, 2025Concise monthly summary for 2025-03 focusing on business value and technical achievements. Delivered a unified Campaign Performance Analysis and Customer Segmentation Platform in H6WU6R/DSA3101-Group-4. Implemented an end-to-end analytics pipeline including data loading, preprocessing, feature engineering, PCA-based clustering, metrics calculation, and visualization to support customer segmentation and campaign performance insights. Integrated the main analysis script with modular components for data processing, EDA, feature engineering, and visualization. Key commits captured core functionality: cc6013983f5045cb6dd279c93c0fb68cfd29c9ae (Create main.py) and d127ff6d2b897067b74bbecae2dab697c804175a (Add files via upload). This work establishes an extensible architecture for marketing analytics, enabling faster insights, repeatable workflows, and data-driven decision making.
March 2025
2 Commits • 1 Features
Mar 1, 2025Concise monthly summary for 2025-03 focusing on business value and technical achievements. Delivered a unified Campaign Performance Analysis and Customer Segmentation Platform in H6WU6R/DSA3101-Group-4. Implemented an end-to-end analytics pipeline including data loading, preprocessing, feature engineering, PCA-based clustering, metrics calculation, and visualization to support customer segmentation and campaign performance insights. Integrated the main analysis script with modular components for data processing, EDA, feature engineering, and visualization. Key commits captured core functionality: cc6013983f5045cb6dd279c93c0fb68cfd29c9ae (Create main.py) and d127ff6d2b897067b74bbecae2dab697c804175a (Add files via upload). This work establishes an extensible architecture for marketing analytics, enabling faster insights, repeatable workflows, and data-driven decision making.
Activity
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Quality Metrics
Correctness90.8%
Maintainability90.8%
Architecture90.8%
Performance87.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVMarkdownPython
Technical Skills
ClusteringData AnalysisData EngineeringData PreprocessingData ProcessingData ScienceData VisualizationDimensionality ReductionDocumentationEconomic ModelingExploratory Data AnalysisExploratory Data Analysis (EDA)Feature EngineeringJupyter NotebooksMachine Learning
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