Designed Modular ETL Pipeline for Email Data

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Designed Modular ETL Pipeline for Email Data

  • Day: 2025-09-30
  • Time: 23:00 to 23:45
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: In Progress
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: ETL, Email Processing, Data Pipeline, SQL, Python

Description

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.

Evidence

  • source_file=2025-09-30.sessions.jsonl, line_number=0, event_count=0, session_id=203b91b188638a76d22997067c6e8e6440f14e8485c71f44cd762a7784302f3a
  • event_ids: []

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