Developed Product Taxonomy and Data Processing Pipeline

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📅 2024-08-28 — Session: Developed Product Taxonomy and Data Processing Pipeline

🕒 21:30–22:15
🏷️ Labels: Data Processing, Product Taxonomy, Feature Engineering, Python, Web Scraping
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to develop a comprehensive product taxonomy and establish a robust data processing pipeline for product comparison and analysis.

Key Activities

  • Merging Data Files: Implemented Python scripts to merge price, product, and store data files, ensuring outputs are saved in the correct directories.
  • Disk Usage Analysis: Utilized the du command to assess disk usage across directories, optimizing storage management.
  • Web Scraping Optimization: Applied limits on store counts in the PreciosClarosSpider class to enhance data scraping efficiency.
  • Product Data Management: Addressed challenges in managing product data using techniques like text normalization, fuzzy matching, and clustering.
  • Product Taxonomy Development: Planned and executed strategies for developing a product taxonomy using classification techniques and KNN, focusing on feature engineering and data preparation.

Achievements

  • Successfully merged diverse data files, optimizing data management.
  • Enhanced web scraping processes by implementing store count limits.
  • Developed a structured approach for product taxonomy and feature engineering, setting the stage for effective product comparison.

Pending Tasks

  • Further refinement of the product taxonomy and feature engineering processes.
  • Implementation and evaluation of the KNN model for product comparison.

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