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fuzzy-item-matching
Use machine learning and the Databricks Lakehouse Platform for product matching that can be used by marketplaces and suppliers for various purposes. Resolve differences between product definitions and descriptions and determine which items are likely pairs and which are distinct across disparate data sets.
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The fuzzy matching isn't tool specific. Using existing quality checks by business low code tools (Rapidminer/Alteryx). E.g. custom text similarity matches for things like vendor/customer names to notify on typo back to ERP. This looks similar to the concept (https://github.com/databricks-industry-solutions/fuzzy-item-matching)
Maybe if I get some free time soon I can formalize into a working example. Been wanting an excuse to try similar concept in delta-rs and polars/duckdb vs databricks/spark vs iceberg/polars.