Data Processing and Model Correction

📅 2025-06-22 — Session: Data Processing and Model Correction

🕒 17:40–18:40
🏷️ Labels: Data_Processing, Python, Modeling, Normalization, Scripts
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The main objective of this session was to enhance data processing scripts and correct data modeling issues.

Key Activities

• Created a combined data table for editorial content, integrating seed ideas with related articles.
• Developed a Python script to merge JSONL files into a DataFrame, focusing on filtering by specific idea IDs.
• Addressed inconsistencies in JSONL data formats, proposing a unified DataFrame for better organization.
• Proposed normalization adjustments for id_digest in data processing scripts to ensure consistency.
• Refactored a Python script for improved data processing, enhancing file handling and coherence of id_digest.
• Resolved merge issues in DataFrames by modifying scripts to include necessary columns from reference files.
• Analyzed and recommended corrections for an academic data model, focusing on relational modeling and normalization.

Achievements

• Improved the robustness and consistency of data processing scripts.
• Enhanced the academic data model by correcting conceptual errors and proposing a relational model using ternary relationships.

Pending Tasks

• Implement the proposed script modifications for merging datasets.
• Finalize the corrected academic data model for implementation.