📅 2025-06-28 — Session: Comprehensive ETL Pipeline Development
🕒 04:55–09:55
🏷️ Labels: ETL, Python, Data Processing, Automation, Financial Reporting
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop and refine an ETL pipeline for financial data processing, including data extraction from Google Sheets, transformation, and CSV report generation.
Key Activities
- Analyzed the AF447 disaster for critical decision points and human factors.
- Reviewed MH370 search developments and aviation theories.
- Compared flight simulation platforms for realism and crash simulation.
- Developed a recipe for Argentine-style salsa criolla.
- Created a systematic approach for coin classification and cleaning.
- Structured an onboarding plan for a financial tracking system.
- Documented ETL flow for financial reporting.
- Created data flow diagrams and Mermaid diagrams for documentation.
- Outlined a one-click ETL and analysis regeneration system.
- Implemented Python scripts for ETL pipeline, focusing on data processing from Google Sheets.
- Addressed issues with PeriodIndex to Datetime conversion and column selection in ETL scripts.
- Resolved ValueError in CSV export and adjusted time period indexing in financial pivot generation.
Achievements
- Successfully developed a comprehensive ETL pipeline script (
run_etl_pipeline.py) for financial data processing, including time series data generation and CSV export. - Enhanced data visualization through automated plot regeneration strategies.
Pending Tasks
- Further enhancements to ETL pipeline with Makefile, scheduler, or Jupyter Notebook version.
- Continue refining data processing scripts for improved efficiency and accuracy.