hpi-sam/ASE-GenAI
Nov 2024 – Nov 2024
1 Month active
Languages Used
SQL
Technical Skills
AI-assisted DevelopmentData AnalysisDatabase Query OptimizationDatabase QueryingSQL
Tonybodo
PROFILE
Tonybodo
Arnold developed an Advanced SQL-based Message Engagement Analytics suite for the hpi-sam/ASE-GenAI repository, delivering a comprehensive set of SQL scripts to analyze messages, likes, and social connections for actionable engagement insights. His approach combined AI-assisted development with data analysis and database query optimization, resulting in task-specific queries, a query plan visualization, and an enhanced broader-network engagement query. Arnold documented the AI-assisted process within a dedicated commit to support future knowledge transfer. The work demonstrated depth through end-to-end delivery, progressing from planning to integration, and addressed the need for deeper analytics on social interaction data using SQL.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
627
Activity Months1
Your Network
20 people
Work History
November 2024
3 Commits • 1 Features
Nov 1, 2024November 2024: Delivered a feature-rich Advanced SQL-based Message Engagement Analytics suite for the hpi-sam/ASE-GenAI project. The feature provides a suite of SQL scripts to analyze messages, likes, and social connections to extract engagement insights, including task-specific queries, a query plan visualization, and an enhanced broader-network engagement query. AI-assisted development notes were included in one dedicated commit to improve traceability and future reuse. End-to-end delivery included three commits that demonstrate progression from planning to AI-assisted development and base integration (7ab6de1fa6a769d93f755778329cfdd6f12ff89f; 4c4d7cffe66a23d3798113fa7ca1c615807dee73; 81a738d4c604a8dd66b9df2afda593391fb30e6d).
3 Commits • 1 Features
Nov 1, 2024November 2024: Delivered a feature-rich Advanced SQL-based Message Engagement Analytics suite for the hpi-sam/ASE-GenAI project. The feature provides a suite of SQL scripts to analyze messages, likes, and social connections to extract engagement insights, including task-specific queries, a query plan visualization, and an enhanced broader-network engagement query. AI-assisted development notes were included in one dedicated commit to improve traceability and future reuse. End-to-end delivery included three commits that demonstrate progression from planning to AI-assisted development and base integration (7ab6de1fa6a769d93f755778329cfdd6f12ff89f; 4c4d7cffe66a23d3798113fa7ca1c615807dee73; 81a738d4c604a8dd66b9df2afda593391fb30e6d).
November 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance66.6%
AI Usage60.0%
Skills & Technologies
Programming Languages
SQL
Technical Skills
AI-assisted DevelopmentData AnalysisDatabase Query OptimizationDatabase QueryingSQL
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