
Developed analytics and data integration solutions across thezachdrake/UMD-INST627-Fall2024 and Prof-Drake-UMD/INST767-Sp25 repositories, focusing on NBA performance analysis and Baltimore-area weather impact assessment. Delivered features such as offensive and defensive metrics dashboards, playoff analysis, and investment categorization using Python, SQL, and Jupyter Notebook. Built end-to-end data pipelines integrating weather, flood, aviation, and housing data, and established scalable project scaffolding with clear documentation. Enhanced project clarity through consolidated README updates, SQL query documentation, and Apache Airflow workflow planning, enabling reproducible pipelines and improved onboarding. Emphasized data storytelling, visualization, and technical writing to support stakeholder decision-making and project maintainability.
August 2025 monthly summary for Prof-Drake-UMD/INST767-Sp25: Focused on documentation consolidation and data pipeline planning for the Big Data Infrastructure Final Project. Delivered updated README content reflecting new data sources and approach, documented SQL queries for Issue 2, outlined DAG/workflow planning for Issue 3, and provided a comprehensive overview of dataset schema, data sources, real-world use cases, and potential data issues. These efforts enhance project clarity, onboarding, and readiness for upcoming milestones, while enabling reproducible data pipelines and clearer stakeholder communication.
August 2025 monthly summary for Prof-Drake-UMD/INST767-Sp25: Focused on documentation consolidation and data pipeline planning for the Big Data Infrastructure Final Project. Delivered updated README content reflecting new data sources and approach, documented SQL queries for Issue 2, outlined DAG/workflow planning for Issue 3, and provided a comprehensive overview of dataset schema, data sources, real-world use cases, and potential data issues. These efforts enhance project clarity, onboarding, and readiness for upcoming milestones, while enabling reproducible data pipelines and clearer stakeholder communication.
This month focused on delivering an end-to-end data integration pipeline for Baltimore-area weather, flood, aviation data, and housing impact analysis, establishing a scalable foundation and documentation. Key outcomes include delivering core features, stabilizing the ingestion pipeline, and scaffolding for future expansion. The work drives business value by enabling data-driven assessments of weather-related housing price shifts and flight disruptions, with ready-to-extend architecture for additional regions.
This month focused on delivering an end-to-end data integration pipeline for Baltimore-area weather, flood, aviation data, and housing impact analysis, establishing a scalable foundation and documentation. Key outcomes include delivering core features, stabilizing the ingestion pipeline, and scaffolding for future expansion. The work drives business value by enabling data-driven assessments of weather-related housing price shifts and flight disruptions, with ready-to-extend architecture for additional regions.
December 2024 monthly summary focusing on key features delivered for the thezachdrake/UMD-INST627-Fall2024 repository. Highlights include Basketball Analytics Notebook Enhancements: playoff analysis, defense/win-rate insights, and investment opportunity categorization. The work emphasizes data-driven decision support, improved narratives, and clearer visuals to support stakeholders in evaluating performance and opportunities.
December 2024 monthly summary focusing on key features delivered for the thezachdrake/UMD-INST627-Fall2024 repository. Highlights include Basketball Analytics Notebook Enhancements: playoff analysis, defense/win-rate insights, and investment opportunity categorization. The work emphasizes data-driven decision support, improved narratives, and clearer visuals to support stakeholders in evaluating performance and opportunities.
Month: 2024-11. Delivered analytics-enabled NBA project components and foundational data access/storytelling templates for the NBA analytics effort. Implemented an Offensive and Defensive Metrics Dashboard with data loading and filtering improvements and visualizations; established a Storytelling Data Template with SQLite data access, basic data querying for games/players, and initial pandas/matplotlib visualizations; refined Narrative and Visualization Storyboard for NBA Playoff storytelling to improve readability while preserving insights. Maintained code quality with clear commit messages and issue mappings (Conaway_issue5, Conaway_issue6, Conaway_issue7).
Month: 2024-11. Delivered analytics-enabled NBA project components and foundational data access/storytelling templates for the NBA analytics effort. Implemented an Offensive and Defensive Metrics Dashboard with data loading and filtering improvements and visualizations; established a Storytelling Data Template with SQLite data access, basic data querying for games/players, and initial pandas/matplotlib visualizations; refined Narrative and Visualization Storyboard for NBA Playoff storytelling to improve readability while preserving insights. Maintained code quality with clear commit messages and issue mappings (Conaway_issue5, Conaway_issue6, Conaway_issue7).

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