ICEI-PUC-Minas-PPL-CDIA/ppl-cd-pcd-sist-int-2025-1-grupo2-disparidade-salarial-2025-1
Mar 2025 – Mar 2025
1 Month active
Languages Used
Markdown
Technical Skills
Data AnalysisDocumentationTechnical Writing
Gabriel Bahia
PROFILE
Gabriel Bahia
Gabriel Bahia enhanced the ICEI-PUC-Minas-PPL-CDIA/ppl-cd-pcd-sist-int-2025-1-grupo2-disparidade-salarial-2025-1 repository by delivering comprehensive documentation updates for the salary disparities research report. He clarified the report’s objectives, scope, audience, and data references, ensuring that analysis and stakeholder engagement were well-supported. Using Markdown for technical writing and documentation, Gabriel consolidated guidance across multiple commits, standardizing the report’s structure and improving governance. His work focused on maintainability and clarity, with no major bugs reported during the period. The result was a stable, well-documented foundation for future data analysis, reflecting strong skills in documentation and technical communication.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
8Total
Bugs
0
Commits
8
Features
1
Lines of code
104
Activity Months1
Your Network
5 people
Work History
March 2025
8 Commits • 1 Features
Mar 1, 2025March 2025 performance summary for the repository ICEI-PUC-Minas-PPL-CDIA/ppl-cd-pcd-sist-int-2025-1-grupo2-disparidade-salarial-2025-1. Delivered documentation improvements for the salary disparities report, clarifying objectives, scope, audience, and data references; strengthened governance and stakeholder engagement; and maintained stability with no major bugs reported.
8 Commits • 1 Features
Mar 1, 2025March 2025 performance summary for the repository ICEI-PUC-Minas-PPL-CDIA/ppl-cd-pcd-sist-int-2025-1-grupo2-disparidade-salarial-2025-1. Delivered documentation improvements for the salary disparities report, clarifying objectives, scope, audience, and data references; strengthened governance and stakeholder engagement; and maintained stability with no major bugs reported.
March 2025
Activity
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Quality Metrics
Correctness97.6%
Maintainability97.6%
Architecture97.6%
Performance95.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Markdown
Technical Skills
Data AnalysisDocumentationTechnical Writing
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