After scraping multiple review sites for sentiment analysis, I’m spending more time cleaning data than analyzing it. Product names come in different formats, prices have random currencies, and specs aren’t standardized. Are there templates or tools that can auto-detect patterns and structure this chaos? Prefer something that integrates with existing scrapers.
Used Latenode’s product data template last week - automatically categorizes specs and converts currencies. Handles 90% of structuring needs out of the box. You can tweak the AI models if needed without coding.
Implement a two-stage processing pipeline: First use regex patterns for obvious patterns (price formats), then train a simple ML model on historical data for ambiguous cases. Open-source tools like OpenRefine work well for the initial cleanup before feeding into AI models.
try pre-built normalization modules from automation marketplaces - saves dev time
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