pcamarillor/O2025_ESI3914O
Aug 2025 – Oct 2025
3 Months active
Languages Used
MarkdownJSONJupyter NotebookPythonSQL
Technical Skills
DocumentationBig Data ProcessingData CleaningData EngineeringData ProcessingData Transformation
Jos
PROFILE
Jos
Over a three-month period, Jose Angel Leon developed and delivered a series of data engineering features in the pcamarillor/O2025_ESI3914O repository, focusing on practical big data workflows. He built hands-on Spark labs for music streaming analytics, bank account operations, and airline data cleaning, using Python, PySpark, and Jupyter Notebooks to demonstrate data processing, schema generation, and transformation techniques. Leon also implemented an end-to-end workflow to ingest CSV data into Neo4j, transforming tabular data into graph structures for downstream analytics. His work emphasized reproducible, well-documented solutions, providing depth in both data engineering and graph database integration without reported defects.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
8Total
Bugs
0
Commits
8
Features
7
Lines of code
2,006
Activity Months3
Your Network
28 people
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025Concise monthly summary for Oct 2025 focusing on delivering an end-to-end data-to-graph ingestion workflow. Implemented Lab06 notebook to ingest CSV data into Neo4j using PySpark, transform data into graph-friendly nodes and edges, persist to Neo4j, and execute relationship queries. This supports downstream graph analytics and business insights.
1 Commits • 1 Features
Oct 1, 2025Concise monthly summary for Oct 2025 focusing on delivering an end-to-end data-to-graph ingestion workflow. Implemented Lab06 notebook to ingest CSV data into Neo4j using PySpark, transform data into graph-friendly nodes and edges, persist to Neo4j, and execute relationship queries. This supports downstream graph analytics and business insights.
October 2025
September 2025
5 Commits • 5 Features
Sep 1, 2025September 2025 highlights: Delivered five hands-on Spark/Data Engineering labs in repo pcamarillor/O2025_ESI3914O to strengthen practical data processing, cleaning, and integration skills. Key features introduced across Lab 01–04 include music streaming data processing, Spark+OOP bank account operations, a dynamic Spark schema generator, airline data cleaning, and data unions/joins across multiple sources. Each lab ships with Jupyter notebooks, examples, and accompanying utility code, all wired to common Spark initialization patterns and reproducible data workflows.
September 2025
5 Commits • 5 Features
Sep 1, 2025September 2025 highlights: Delivered five hands-on Spark/Data Engineering labs in repo pcamarillor/O2025_ESI3914O to strengthen practical data processing, cleaning, and integration skills. Key features introduced across Lab 01–04 include music streaming data processing, Spark+OOP bank account operations, a dynamic Spark schema generator, airline data cleaning, and data unions/joins across multiple sources. Each lab ships with Jupyter notebooks, examples, and accompanying utility code, all wired to common Spark initialization patterns and reproducible data workflows.
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025 — pcamarillor/O2025_ESI3914O: Key feature delivered: a new Markdown profile for collaborator Jose Angel Leon, including personal bio, location, current work, and contact information; also standardized the filename for consistency. No major bugs fixed this month. Overall impact: improved contributor visibility, onboarding, and collaboration with external partners; stronger governance and discoverability of contributor profiles. Technologies/skills demonstrated: Markdown-based content authoring, profile standardization, version-control hygiene, and commit traceability. Business value: faster external outreach, clearer attribution, and more consistent contributor documentation.
2 Commits • 1 Features
Aug 1, 2025August 2025 — pcamarillor/O2025_ESI3914O: Key feature delivered: a new Markdown profile for collaborator Jose Angel Leon, including personal bio, location, current work, and contact information; also standardized the filename for consistency. No major bugs fixed this month. Overall impact: improved contributor visibility, onboarding, and collaboration with external partners; stronger governance and discoverability of contributor profiles. Technologies/skills demonstrated: Markdown-based content authoring, profile standardization, version-control hygiene, and commit traceability. Business value: faster external outreach, clearer attribution, and more consistent contributor documentation.
August 2025
Activity
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Quality Metrics
Correctness87.6%
Maintainability87.6%
Architecture87.6%
Performance85.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPythonSQL
Technical Skills
Big Data ProcessingData CleaningData EngineeringData ProcessingData TransformationDocumentationGraph DatabasesJupyter NotebookJupyter NotebooksNeo4jObject-Oriented ProgrammingPySparkPythonSchema DefinitionSpark
Repositories Contributed To
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