Enhanced email and WhatsApp data processing pipelines

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Enhanced email and WhatsApp data processing pipelines

  • Day: 2025-10-23
  • Time: 14:20 to 15:30
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Email Processing, Whatsapp, Data Normalization, Python, Data Integrity

Description

Session Goal: The session aimed to enhance the data processing pipelines for both email and WhatsApp data, focusing on normalization, schema compliance, and error handling.

Key Activities:

  • Developed and executed a Python script for email normalization, ensuring structured output in a quartet format.
  • Addressed schema mismatch errors in CSV processing for email data, updating code to align with new schema requirements.
  • Conducted a review of email data processing, identifying and fixing issues with timestamp population and participant schema.
  • Implemented bug fixes and improvements to the email CSV processing script, enhancing participant tracking and timestamp handling.
  • Explored WhatsApp data processing queries, focusing on adapter design and data cleaning strategies.
  • Planned and executed a hardening plan for the WhatsApp pipeline, ensuring schema compliance and data integrity.
  • Developed a script to normalize WhatsApp text exports into a structured CSV format, considering edge cases for participant identification.
  • Addressed issues with WA adapter data handling, implementing fixes for JID normalization and data integrity.
  • Corrected handle ID processing for WhatsApp data, ensuring valid phone formats and data integrity.

Achievements:

  • Successfully normalized email and WhatsApp data, ensuring schema compliance and improved data integrity.
  • Enhanced error handling and robustness of data processing scripts for both email and WhatsApp pipelines.

Pending Tasks:

  • Further testing and validation of the updated scripts to ensure stability and performance in production environments.
  • Continuous monitoring and refinement of data processing pipelines to address any emerging issues.

Evidence

  • source_file=2025-10-23.sessions.jsonl, line_number=3, event_count=0, session_id=c742a09ad3602f5c91ff815b349c221ff39f0ffb6dcec9319bf427b5bed66cc1
  • event_ids: []

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