📅 2025-10-23 — Session: Enhanced email and WhatsApp data processing pipelines
🕒 14:20–15:30
🏷️ Labels: Email Processing, Whatsapp, Data Normalization, Python, Data Integrity
📂 Project: Dev
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.