Developed data ingestion pipeline with keyword extraction

• Day: 2024-10-02
• Time: 03:35 to 04:10
• Project: Dev
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Data Ingestion, Keyword Extraction, Classification, Automation, Sqlite

Description

Session Goal

The session aimed to develop a data ingestion pipeline integrating keyword extraction and classification to organize data from various sources like RSS feeds and emails.

Key Activities

• Developed a NewsDataCollector to parse news into a SQLite database.
• Planned and executed steps for keyword extraction and classification layers.
• Designed a triage system for data classification, defining categories and routing data based on document types and keywords.
• Outlined an email processing system to detect new messages and perform triage to extract metadata.
• Addressed a query timeout issue during email processing, suggesting alternative approaches for loading emails.
• Provided Python code for loading email data from a SQLite database into a Pandas DataFrame for analysis.

Achievements

• Successfully integrated keyword extraction and classification into the data ingestion pipeline.
• Developed a structured approach for data triage and email processing.
• Resolved technical issues related to query timeouts during email processing.

Pending Tasks

• Enhance data handling workflows for better performance and efficiency.
• Further development of keyword extraction and classification layers.
• Optimization of the email processing system to handle larger datasets efficiently.

Evidence

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• event_ids: []