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EntityMatcher - Match, transform or categorize data automatically | Product Hunt

 4 months ago
source link: https://www.producthunt.com/posts/entitymatcher
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Match, transform or categorize data automatically

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Hi Product Hunters, I’m excited to launch my first product here!

I’ve spent way too many hours of my life dealing with messy datasets, so I built EntityMatcher to help technical and non-technical users automatically clean their data without the need to write and maintain complex rule sets.

Tasks ------ 🏷️ Categorize - Tagging or bucketing your data (e.g. this product is furniture or this piece of text is about travel)

👥 Match - Figuring out if two entities (people, places, products, businesses, etc.) are the same for things de-duplicating or joining datasets

🔄 Transform - Extracting and reformatting values (e.g. “find the phone number in this text field and format it like ”)

Example Use Cases -------------------- 📚 Researchers with qualitative data can “code” this data using categorization without a ton of manual effort

🌐 Anyone dealing with web scraped data can use transform to consistently structure that data no matter how often the page changes

🛒 E-commerce companies can use matching to maintain a clean product list no matter how different their vendor naming conventions are and the use categorization to organize those products automatically

💳 Fintech companies can use matching to ensure a particular transaction belongs to the right vendor and then group those transactions together using categorization for further analysis

How does it work ----------------- EntityMatcher uses LLMs to handle the variation inherent to messy data that can be difficult for deterministic rule sets to deal with. Users customize the system to their own use case by providing free text instructions and some examples, both of which can easily be done in the UI.

Where can I use it? ------------------- Wherever is most comfortable for you (UI, API, Google Sheets Plugin), see our docs for more info: docs.entitymatcher.com

I’d love any feedback you all have, and if you need some help cleaning your data, please let me know!


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