pcamarillor/O2025_ESI3914B
Aug 2025 – Oct 2025
3 Months active
Languages Used
Jupyter NotebookPythonJSONSQL
Technical Skills
Data AnalysisJupyter NotebookJupyter NotebooksPython ProgrammingBig DataBig Data Processing
Carolina Arellano
PROFILE
Carolina Arellano
Ana Arellano developed a suite of data engineering and analytics solutions for the pcamarillor/O2025_ESI3914B repository over three months, focusing on robust, reusable Jupyter Notebooks. She built Python and PySpark workflows for playlist analysis, financial utilities, and airline data transformation, emphasizing data de-duplication, schema generation, and validation. Ana integrated Spark SQL and Power BI for end-to-end analytics, and implemented a Neo4j data ingestion pipeline for graph-based subway network analysis. Her work featured thorough testing, clear documentation, and maintainable code, enabling reliable onboarding and future extension. The depth of her engineering addressed both data quality and stakeholder usability.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
14Total
Bugs
0
Commits
14
Features
6
Lines of code
2,204
Activity Months3
Your Network
40 people
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for developer work on repository pcamarillor/O2025_ESI3914B. Delivered a new data ingestion notebook and established end-to-end validation for a Neo4j graph pipeline using Vienna subway network data.
1 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for developer work on repository pcamarillor/O2025_ESI3914B. Delivered a new data ingestion notebook and established end-to-end validation for a Neo4j graph pipeline using Vienna subway network data.
October 2025
September 2025
11 Commits • 4 Features
Sep 1, 2025September 2025 performance: Delivered critical features across financial utilities and data engineering, with strong emphasis on reliability, onboarding, and stakeholder value. Key outcomes include a robust BankAccount utility with validation and error handling, reusable Spark schema tooling and Spark SQL notebooks, end-to-end PySpark data cleaning/transformation workflows for airline data, and integrated rental analytics with data unions/joins plus a Power BI dashboard. All work was paired with proper testing and refactoring to improve maintainability and quality.
September 2025
11 Commits • 4 Features
Sep 1, 2025September 2025 performance: Delivered critical features across financial utilities and data engineering, with strong emphasis on reliability, onboarding, and stakeholder value. Key outcomes include a robust BankAccount utility with validation and error handling, reusable Spark schema tooling and Spark SQL notebooks, end-to-end PySpark data cleaning/transformation workflows for airline data, and integrated rental analytics with data unions/joins plus a Power BI dashboard. All work was paired with proper testing and refactoring to improve maintainability and quality.
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary: Delivered Lab 01 Playlist Analysis Notebook for repo pcamarillor/O2025_ESI3914B. Implemented data processing features to de-duplicate listening records, compute per-user unique song counts, and identify the most popular song using Python collections. Added clarifying comments and minor improvements to enhance readability and maintainability. No major bugs fixed this month; focus remained on delivering a reusable analytics notebook and a clear, reviewable artifact.
2 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary: Delivered Lab 01 Playlist Analysis Notebook for repo pcamarillor/O2025_ESI3914B. Implemented data processing features to de-duplicate listening records, compute per-user unique song counts, and identify the most popular song using Python collections. Added clarifying comments and minor improvements to enhance readability and maintainability. No major bugs fixed this month; focus remained on delivering a reusable analytics notebook and a clear, reviewable artifact.
August 2025
Activity
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Quality Metrics
Correctness85.0%
Maintainability85.0%
Architecture81.4%
Performance72.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJupyter NotebookPythonSQL
Technical Skills
Big DataBig Data ProcessingData AnalysisData EngineeringData IngestionData TransformationData VisualizationGraph DatabasesJSON ProcessingJupyter NotebookJupyter NotebooksNeo4jNotebook ManagementObject-Oriented ProgrammingPySpark
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