pcamarillor/O2025_ESI3914O
Sep 2025 – Oct 2025
2 Months active
Languages Used
JSONJupyter NotebookMarkdownPythonSQL
Technical Skills
Apache SparkBig Data ProcessingData AnalysisData EngineeringData StructuresDataFrames
EduNav04
PROFILE
Edunav04
Eduardo Navarro Martínez developed robust data engineering solutions in the pcamarillor/O2025_ESI3914O repository, focusing on end-to-end pipelines for both tabular and graph data. He built Spark-based workflows for schema-aware processing, JSON handling, and partitioned outputs, leveraging Python and Spark SQL to improve data quality and reproducibility. Eduardo also integrated Neo4j, designing a pipeline that transformed patient and doctor records into graph structures for analytics, with data integrity verified through PySpark. His work included enhancing schema utilities to support broader data types and documenting collaboration profiles, demonstrating depth in ETL, data analysis, and graph database integration within Jupyter Notebooks.
Overall Statistics
Feature vs Bugs
83%Features
Repository Contributions
10Total
Bugs
1
Commits
10
Features
5
Lines of code
2,936
Activity Months2
Your Network
15 people
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025Monthly work summary for 2025-10: Delivered an end-to-end graph analytics data pipeline lab (Lab06) and reinforced data integrity checks, enabling graph-based insights while showcasing strong data engineering and analytics capabilities.
1 Commits • 1 Features
Oct 1, 2025Monthly work summary for 2025-10: Delivered an end-to-end graph analytics data pipeline lab (Lab06) and reinforced data integrity checks, enabling graph-based insights while showcasing strong data engineering and analytics capabilities.
October 2025
September 2025
9 Commits • 4 Features
Sep 1, 2025Concise monthly summary for 2025-09 focusing on key features delivered, major bugs fixed, impact, and technologies demonstrated. Highlights include Spark Lab Lab04 with SparkSQL and schema utilities, Lab01 playlist data analysis, BankAccount Spark integration demo, and collaboration profile documentation. Major bugs fixed include schema generation enhancements to Spark utilities ensuring broader type support. Overall impact includes robust end-to-end data processing pipelines, improved data quality and reproducibility, and strengthened developer branding. Key outcomes: - End-to-end Spark Lab04 pipeline delivering schema-aware processing, JSON handling, joins, and outputs to Parquet and CSV partitioned by agency. - Deduplicated playlist analysis and most-played song insights in Lab01 notebook. - BankAccount class with deposits/withdrawals demonstrated in notebook, showcasing Spark integration. - Updated collaborator profile documenting Eduardo Navarro Martínez for professional networking. - Improved Spark utilities with broader data type support and error resilience.
September 2025
9 Commits • 4 Features
Sep 1, 2025Concise monthly summary for 2025-09 focusing on key features delivered, major bugs fixed, impact, and technologies demonstrated. Highlights include Spark Lab Lab04 with SparkSQL and schema utilities, Lab01 playlist data analysis, BankAccount Spark integration demo, and collaboration profile documentation. Major bugs fixed include schema generation enhancements to Spark utilities ensuring broader type support. Overall impact includes robust end-to-end data processing pipelines, improved data quality and reproducibility, and strengthened developer branding. Key outcomes: - End-to-end Spark Lab04 pipeline delivering schema-aware processing, JSON handling, joins, and outputs to Parquet and CSV partitioned by agency. - Deduplicated playlist analysis and most-played song insights in Lab01 notebook. - BankAccount class with deposits/withdrawals demonstrated in notebook, showcasing Spark integration. - Updated collaborator profile documenting Eduardo Navarro Martínez for professional networking. - Improved Spark utilities with broader data type support and error resilience.
Activity
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Quality Metrics
Correctness82.0%
Maintainability80.0%
Architecture76.0%
Performance74.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPythonSQL
Technical Skills
Apache SparkBig Data ProcessingData AnalysisData EngineeringData StructuresDataFramesDocumentationETLGraph DatabasesJSON ProcessingJupyter NotebookJupyter NotebooksNeo4jObject-Oriented ProgrammingPySpark
Repositories Contributed To
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