📅 2025-09-30 — Session: Designed Modular ETL Pipeline for Email Data
🕒 23:00–23:45
🏷️ Labels: ETL, Email Processing, Data Pipeline, SQL, Python
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to design a modular ETL pipeline for processing email data, focusing on creating reusable components for data ingestion, normalization, and analysis.
Key Activities
- Blueprint Creation: Outlined a structured approach to refactor EDA of email data into modular ETL components, detailing each step’s function and potential pitfalls.
- Artifact Development: Developed SQL functions and views for email data processing, including normalization and response metrics, along with a Python bootstrap script.
- Pandas Pipeline: Created a comprehensive email processing pipeline using pandas, handling normalization, role splitting, and reply matching.
- Network Analysis: Designed pandas-based functions for email network analysis, including building edge tables and calculating metrics.
- Database Setup: Explored setting up a database using Supabase or local Postgres for managing email data.
Achievements
- Successfully outlined a modular ETL pipeline design for email data.
- Developed SQL and Python artifacts for executing email data processing tasks.
- Implemented a pandas-first approach for email processing and network analysis.
Pending Tasks
- Finalize the integration of the ETL components into a cohesive pipeline.
- Test the database setup for email data management using Supabase or local Postgres.