In this project, I collected key product data from Zalando UK's "Men" category. All products, including their variants, were scraped and stored in a custom SQLite3 database. Each record is unique, with stock status converted to boolean values, and no null columns.

Scraped all products (and their variants) from the "Men" category on zalando.co.uk.

Extracted essential data fields: sku, brand, product name, variant sku, price, stock availability, colour, images, description, and URL.

Eliminated duplicate entries by processing variant skus uniquely while retaining a consistent product sku.

Converted stock statuses to true/false rather than text labels.

Structured and stored the data into a robust SQLite3 database with over 65,000 products.

This project delivered a comprehensive, clean dataset of Zalando’s 'Men' category products, offering valuable insights for market research, competitive analysis, and pricing strategy. The dataset enables businesses to track product trends, monitor stock availability, and analyze customer preferences across multiple attributes.