Developed and Enhanced Data Processing Pipelines

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📅 2024-08-28 — Session: Developed and Enhanced Data Processing Pipelines

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

Session Goal

The session aimed to develop and enhance data processing pipelines for managing and analyzing product data efficiently.

Key Activities

  1. Scripts for Merging Data Files: Implemented Python scripts to merge price, product, and store data files, ensuring outputs are saved in the correct directories.
  2. Disk Usage Monitoring: Utilized the du command to check disk usage, ensuring efficient storage management.
  3. Web Scraping Limits: Applied limits on the number of stores per chain in the PreciosClarosSpider class to optimize web scraping.
  4. Product Data Challenges: Addressed challenges in managing product data using techniques like text normalization, fuzzy matching, and clustering.
  5. Product Taxonomy and Feature Engineering: Developed a product taxonomy and implemented KNN for product comparison, focusing on feature engineering and data preparation.
  6. Data Processing and Analysis Pipeline: Outlined a comprehensive plan for data processing, including feature engineering, data preparation, and statistical analysis.

Achievements

  • Successfully merged data files and monitored disk usage.
  • Optimized web scraping processes.
  • Developed strategies for product data management and taxonomy development.

Pending Tasks

  • Continue refining feature engineering techniques.
  • Further evaluate and test the data processing pipeline.

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