pcamarillor/O2025_ESI3914B
Aug 2025 – Oct 2025
3 Months active
Languages Used
MarkdownJSONJupyter NotebookPythonSQL
Technical Skills
DocumentationApache SparkBig Data ProcessingClass DesignData AnalysisData Cleaning
Santiago Montes de Oca
PROFILE
Santiago Montes De Oca
Santiago Montes de Oca developed a series of data engineering solutions for the pcamarillor/O2025_ESI3914B repository, focusing on practical workflows in big data and analytics. Over three months, he built Jupyter notebooks and Python utilities for data cleaning, transformation, and analysis using Apache Spark and PySpark, including pipelines for deduplicating records, joining datasets, and feature engineering. He implemented end-to-end flows such as ingesting IP data into Neo4j graphs and real-time log monitoring with Structured Streaming, providing hands-on experience with both batch and streaming data. His work emphasized maintainable code, clear documentation, and reproducible results, demonstrating solid technical depth.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
14Total
Bugs
0
Commits
14
Features
9
Lines of code
3,641
Activity Months3
Your Network
40 people
Work History
October 2025
3 Commits • 2 Features
Oct 1, 2025October 2025 performance summary for repository pcamarillor/O2025_ESI3914B. Delivered end-to-end data ingestion and real-time monitoring enhancements through two notebooks, enabling practical hands-on experience with graph data and operational alerts. Established end-to-end data flow: Spark-based ingestion of IP data to a Neo4j graph with a verification query, and Structured Streaming for server logs with alerting. Added testing and traceability artifacts including a random log generator and updated notebook metadata.
3 Commits • 2 Features
Oct 1, 2025October 2025 performance summary for repository pcamarillor/O2025_ESI3914B. Delivered end-to-end data ingestion and real-time monitoring enhancements through two notebooks, enabling practical hands-on experience with graph data and operational alerts. Established end-to-end data flow: Spark-based ingestion of IP data to a Neo4j graph with a verification query, and Structured Streaming for server logs with alerting. Added testing and traceability artifacts including a random log generator and updated notebook metadata.
October 2025
September 2025
10 Commits • 6 Features
Sep 1, 2025September 2025 performance summary for repository pcamarillor/O2025_ESI3914B. Focused on delivering hands-on data engineering notebooks and utilities that underscore data cleaning, transformation, and analytics capabilities across Spark and Python, while improving maintainability and documentation.
September 2025
10 Commits • 6 Features
Sep 1, 2025September 2025 performance summary for repository pcamarillor/O2025_ESI3914B. Focused on delivering hands-on data engineering notebooks and utilities that underscore data cleaning, transformation, and analytics capabilities across Spark and Python, while improving maintainability and documentation.
August 2025
1 Commits • 1 Features
Aug 1, 2025August 2025: pcamarillor/O2025_ESI3914B focused on strengthening contributor onboarding and collaboration visibility through targeted documentation improvements. Delivered a new contributor introduction markdown file (santiago_mdeo.md) that clearly presents contributor identity, nickname origin, and collaboration norms within the repository. The change is recorded under commit 5278cd4bb6ede8158d90b0dc44569917d7fc2fd2, ensuring traceability. No code changes or bug fixes were implemented this month.
1 Commits • 1 Features
Aug 1, 2025August 2025: pcamarillor/O2025_ESI3914B focused on strengthening contributor onboarding and collaboration visibility through targeted documentation improvements. Delivered a new contributor introduction markdown file (santiago_mdeo.md) that clearly presents contributor identity, nickname origin, and collaboration norms within the repository. The change is recorded under commit 5278cd4bb6ede8158d90b0dc44569917d7fc2fd2, ensuring traceability. No code changes or bug fixes were implemented this month.
August 2025
Activity
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Quality Metrics
Correctness82.8%
Maintainability81.4%
Architecture80.0%
Performance77.2%
AI Usage22.8%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPythonSQL
Technical Skills
Apache SparkBig Data ProcessingClass DesignData AnalysisData CleaningData EngineeringData ProcessingData TransformationDocumentationFeature EngineeringGraph DatabasesJupyter NotebookJupyter NotebooksLog AnalysisMethod Implementation
Repositories Contributed To
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