ITACADEMYprojectes/ProjecteData
Feb 2025 – Mar 2025
2 Months active
Languages Used
CSVMarkdownExcelJupyter NotebookPythonSQL
Technical Skills
Data AnalysisData EngineeringDocumentationData Analysis DocumentationData BackupData Cleaning
Evelyn
PROFILE
Evelyn
Evelyn Antelo contributed to the ITACADEMYprojectes/ProjecteData repository by developing data analytics and reliability features focused on business reporting and data quality. She built and enhanced EDA modules, KPI dashboards, and data export pipelines using Python, Pandas, and SQL, enabling faster insights and more consistent reporting. Her work included implementing data cleaning, deduplication, and backup processes, as well as creating Jupyter Notebooks for exploratory analysis. By addressing null handling and restoring critical files, Evelyn improved data integrity and reproducibility. The depth of her contributions ensured robust data governance, streamlined workflows, and reliable analytics infrastructure for ongoing business intelligence needs.
Overall Statistics
Feature vs Bugs
84%Features
Repository Contributions
60Total
Bugs
4
Commits
60
Features
21
Lines of code
114,504
Activity Months2
Your Network
36 people
Work History
March 2025
57 Commits • 19 Features
Mar 1, 2025March 2025 monthly summary for ITACADEMYprojectes/ProjecteData: Delivered a broad set of data analytics features and reliability improvements across EDA CX and KPI tooling, with a strong focus on business value, data quality, and reporting consistency. Key features delivered: - EDA CX enhancements and dashboard updates: core data processing improvements, null handling, and dashboard/chart updates culminating in a finalized EDA CX module. - KPI dashboards: created KPIs.pbix; weekly KPI integration and updates; added radar chart and comparison visuals to enable faster performance monitoring. - Data governance and export: updated variable dictionary and enabled clean data export to Data storage. - Data integrity and reliability: restored files after an issue; established backups folder for database backups; implemented weekly database backup and base load. - S4 and analytics enhancements: core improvements for S4 module including metrics and reporting; consolidated demand trends and annual variation reporting; improved presentation assets. - Data quality improvements: deduplication fixes and data cleaning enhancements across EDA CX. Major bugs fixed: - Deduplication logic corrected; duplicates counted accurately and data cleaning updated. - Null handling in EDA CX data processing corrected to prevent downstream errors. - Resolved file availability issues through restoration efforts. Overall impact and accomplishments: - Significantly improved data quality, reliability, and governance, enabling more accurate KPI reporting and faster time-to-insights. - Reduced manual data cleanup and ensured consistent, auditable data lineage across dashboards and reports. - Strengthened business decision support with standardized KPI visuals and robust data exports. Technologies/skills demonstrated: - Data engineering: deduplication, data cleaning, dictionary management, and data export pipelines. - BI and analytics: EDA CX dashboards, KPI PBIX, radar charts, and results presentations. - Data reliability and governance: backups, file restoration, and data processing improvements. - S4 module capabilities: metrics, forecasting/trends, and enhanced reporting.
57 Commits • 19 Features
Mar 1, 2025March 2025 monthly summary for ITACADEMYprojectes/ProjecteData: Delivered a broad set of data analytics features and reliability improvements across EDA CX and KPI tooling, with a strong focus on business value, data quality, and reporting consistency. Key features delivered: - EDA CX enhancements and dashboard updates: core data processing improvements, null handling, and dashboard/chart updates culminating in a finalized EDA CX module. - KPI dashboards: created KPIs.pbix; weekly KPI integration and updates; added radar chart and comparison visuals to enable faster performance monitoring. - Data governance and export: updated variable dictionary and enabled clean data export to Data storage. - Data integrity and reliability: restored files after an issue; established backups folder for database backups; implemented weekly database backup and base load. - S4 and analytics enhancements: core improvements for S4 module including metrics and reporting; consolidated demand trends and annual variation reporting; improved presentation assets. - Data quality improvements: deduplication fixes and data cleaning enhancements across EDA CX. Major bugs fixed: - Deduplication logic corrected; duplicates counted accurately and data cleaning updated. - Null handling in EDA CX data processing corrected to prevent downstream errors. - Resolved file availability issues through restoration efforts. Overall impact and accomplishments: - Significantly improved data quality, reliability, and governance, enabling more accurate KPI reporting and faster time-to-insights. - Reduced manual data cleanup and ensured consistent, auditable data lineage across dashboards and reports. - Strengthened business decision support with standardized KPI visuals and robust data exports. Technologies/skills demonstrated: - Data engineering: deduplication, data cleaning, dictionary management, and data export pipelines. - BI and analytics: EDA CX dashboards, KPI PBIX, radar charts, and results presentations. - Data reliability and governance: backups, file restoration, and data processing improvements. - S4 module capabilities: metrics, forecasting/trends, and enhanced reporting.
March 2025
February 2025
3 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for ITACADEMYprojectes/ProjecteData: Delivered foundational data readiness and testing infrastructure in Equip_E, enabling faster experimentation and reliable test artifact management. Two new features were implemented: 1) Equip_E: Test artifact lifecycle — added EV_test.md to support testing and cleanup of artifacts; cleanup removed a stray test push to keep the repo clean. 2) Equip_E: Data exploration setup for tourist accommodations — added a sample dataset under Equip_E/Data and created an initial Jupyter notebook to kick off data analysis and ML work. No major bugs fixed this month; minor housekeeping improvements contributed to a cleaner codebase. Overall impact: improved reproducibility, faster experimentation for ML tasks, and clearer data exploration workflows; demonstrated skills in dataset management, notebook-based exploration, and Git hygiene.
February 2025
3 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for ITACADEMYprojectes/ProjecteData: Delivered foundational data readiness and testing infrastructure in Equip_E, enabling faster experimentation and reliable test artifact management. Two new features were implemented: 1) Equip_E: Test artifact lifecycle — added EV_test.md to support testing and cleanup of artifacts; cleanup removed a stray test push to keep the repo clean. 2) Equip_E: Data exploration setup for tourist accommodations — added a sample dataset under Equip_E/Data and created an initial Jupyter notebook to kick off data analysis and ML work. No major bugs fixed this month; minor housekeeping improvements contributed to a cleaner codebase. Overall impact: improved reproducibility, faster experimentation for ML tasks, and clearer data exploration workflows; demonstrated skills in dataset management, notebook-based exploration, and Git hygiene.
Activity
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Quality Metrics
Correctness82.8%
Maintainability82.8%
Architecture76.6%
Performance76.2%
AI Usage22.6%
Skills & Technologies
Programming Languages
CSVExcelJupyter NotebookMarkdownPythonSQL
Technical Skills
Data AnalysisData Analysis DocumentationData BackupData CleaningData EngineeringData EntryData ExportData ManagementData ManipulationData PreparationData PreprocessingData VisualizationData WranglingDatabase ConnectionDatabase Management
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