BigData2025-Rev/p3
Jan 2025 – Feb 2025
2 Months active
Languages Used
MarkdownPythonSQL
Technical Skills
Data EngineeringData MergingData ProcessingData TransformationData WranglingDocumentation
walleaka
PROFILE
Walleaka
Kish Aka developed and maintained an end-to-end data wrangling pipeline for the BigData2025-Rev/p3 repository, focusing on 2000s census data. Over two months, Kish engineered a reproducible workflow that automated FTP and MDB data acquisition, merged CSVs using PySpark, and consolidated outputs into ORC formats. He improved onboarding and maintainability by establishing standardized scaffolding and documentation. Kish also enhanced data preprocessing accuracy, refactored path handling for header parsing, and delivered analytical scripts for district population analysis using Python and SQL. His work modernized Power BI reporting and ensured scalable, maintainable analytics, demonstrating depth in data engineering and collaborative BI development.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
12Total
Bugs
1
Commits
12
Features
4
Lines of code
2,544
Activity Months2
Your Network
16 people
Work History
February 2025
6 Commits • 2 Features
Feb 1, 2025February 2025 performance highlights for BigData2025-Rev/p3 focused on fixing data ingestion accuracy, delivering scalable analytics, and modernizing BI reporting, with emphasis on business value and maintainable code. The month delivered improved data quality, reproducible census-year analyses, and enhanced Power BI dashboards to support decision-making.
6 Commits • 2 Features
Feb 1, 2025February 2025 performance highlights for BigData2025-Rev/p3 focused on fixing data ingestion accuracy, delivering scalable analytics, and modernizing BI reporting, with emphasis on business value and maintainable code. The month delivered improved data quality, reproducible census-year analyses, and enhanced Power BI dashboards to support decision-making.
February 2025
January 2025
6 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for BigData2025-Rev/p3 focused on delivering a robust end-to-end wrangling solution for 2000s census data and establishing a maintainable scaffolding foundation for future wrangling work. Key outcomes include a reproducible data pipeline from FTP/MDB data acquisition through PySpark-based merging of CSVs across 'first', 'second', and 'geo' files, and consolidation into ORC formats, plus final-wrangler scaffolding and cleanup to standardize the 2000s wrangling workflow and reduce maintenance overhead. These efforts enable faster data ingestion, improved analytics performance, and clearer on-boarding for new contributors, aligning with the team's data architecture and analytics goals.
January 2025
6 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for BigData2025-Rev/p3 focused on delivering a robust end-to-end wrangling solution for 2000s census data and establishing a maintainable scaffolding foundation for future wrangling work. Key outcomes include a reproducible data pipeline from FTP/MDB data acquisition through PySpark-based merging of CSVs across 'first', 'second', and 'geo' files, and consolidation into ORC formats, plus final-wrangler scaffolding and cleanup to standardize the 2000s wrangling workflow and reduce maintenance overhead. These efforts enable faster data ingestion, improved analytics performance, and clearer on-boarding for new contributors, aligning with the team's data architecture and analytics goals.
Activity
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Quality Metrics
Correctness89.2%
Maintainability88.4%
Architecture89.2%
Performance88.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonSQL
Technical Skills
Data AnalysisData EngineeringData MergingData PreprocessingData ProcessingData TransformationData WranglingDocumentationETLFTP ClientFile HandlingFile ManagementFile ParsingFile System OperationsPandas
Repositories Contributed To
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