
Over a three-month period, contributed to the pcamarillor/O2025_ESI3914B repository by developing eight new features focused on data engineering and educational tooling. Built a UK train station data ingestion pipeline integrating PySpark and Neo4j, enabling CSV-to-graph transformations and verification queries. Enhanced lab reproducibility and onboarding through standardized contributor documentation and lab templates. Delivered a bank account management module and playlist analysis notebook, demonstrating Python module development and data analysis techniques. Introduced structured streaming for log processing using Spark, supporting real-time monitoring. Work emphasized maintainability, onboarding efficiency, and hands-on big data processing with Python, Spark SQL, and Jupyter Notebooks.
Month: 2025-10 — Delivered end-to-end data ingestion, visualization, and streaming capabilities in pcamarillor/O2025_ESI3914B. Implemented UK Train Station Data Ingestion Pipeline (PySpark + Neo4j) for CSV-to-graph ingestion with PySpark verification queries. Enhanced notebook visuals with an embedded image in Markdown. Launched Structured Streaming for log processing (directory-based ingestion, parsing, critical-error filtering, console output). Major bugs fixed: none reported; existing components stabilized. Technologies demonstrated: PySpark, Neo4j, Spark Structured Streaming, CSV parsing, graph data modeling, and notebook data storytelling.
Month: 2025-10 — Delivered end-to-end data ingestion, visualization, and streaming capabilities in pcamarillor/O2025_ESI3914B. Implemented UK Train Station Data Ingestion Pipeline (PySpark + Neo4j) for CSV-to-graph ingestion with PySpark verification queries. Enhanced notebook visuals with an embedded image in Markdown. Launched Structured Streaming for log processing (directory-based ingestion, parsing, critical-error filtering, console output). Major bugs fixed: none reported; existing components stabilized. Technologies demonstrated: PySpark, Neo4j, Spark Structured Streaming, CSV parsing, graph data modeling, and notebook data storytelling.
September 2025: Delivered lab enhancements across pcamarillor/O2025_ESI3914B, increasing reproducibility and instructional value. Key features delivered include the Bank Account Management Module with a new bank_class.py and notebook integration (deposits, withdrawals, balance checks) and notebook refresh via importlib; Lab 01 Playlist Analysis Notebook with end-to-end playlist analytics (duplicate removal, per-user unique song counts, popular songs) and sample data; Notebook Cleanup and Lab Templates to standardize language sections and support submission workflows; Spark Lab enhancements including Celsius-Fahrenheit MapReduce exercise, SparkUtils utilities, and improved schema generation for Spark SQL workflows. No major bugs reported this month; minor cleanup tasks completed. Overall impact: more scalable labs, faster onboarding, and richer data-processing demonstrations for students. Technologies demonstrated: Python module development, importlib-based notebook refresh, enhanced notebook workflows, and Spark (Spark SQL, MapReduce, schema utilities).
September 2025: Delivered lab enhancements across pcamarillor/O2025_ESI3914B, increasing reproducibility and instructional value. Key features delivered include the Bank Account Management Module with a new bank_class.py and notebook integration (deposits, withdrawals, balance checks) and notebook refresh via importlib; Lab 01 Playlist Analysis Notebook with end-to-end playlist analytics (duplicate removal, per-user unique song counts, popular songs) and sample data; Notebook Cleanup and Lab Templates to standardize language sections and support submission workflows; Spark Lab enhancements including Celsius-Fahrenheit MapReduce exercise, SparkUtils utilities, and improved schema generation for Spark SQL workflows. No major bugs reported this month; minor cleanup tasks completed. Overall impact: more scalable labs, faster onboarding, and richer data-processing demonstrations for students. Technologies demonstrated: Python module development, importlib-based notebook refresh, enhanced notebook workflows, and Spark (Spark SQL, MapReduce, schema utilities).
August 2025 — Focused on improving contributor onboarding and repository collaboration in pcamarillor/O2025_ESI3914B. Delivered contributor profile documentation and established a collaborator profile to streamline future contributions. No major bugs were reported this month. The work enhances transparency, onboarding, and long-term maintainability of the project.
August 2025 — Focused on improving contributor onboarding and repository collaboration in pcamarillor/O2025_ESI3914B. Delivered contributor profile documentation and established a collaborator profile to streamline future contributions. No major bugs were reported this month. The work enhances transparency, onboarding, and long-term maintainability of the project.

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