marketplace product category codes

Portuguese-named category labels in the Olist translation table that flag which orders belong to home-furnishings lines - notably furniture_decor, bed_bath_table and housewares.

Joining on this table is how furniture subsets are carved out of the broader marketplace dump.

In this catalog it appears concretely: - Brazilian E-Commerce Public Dataset by Olist — "the product category table includes furniture_decor, bed_bath_table and housewares".

Conventions decide whether two sources can be joined at all. Buy one side of an analysis that ignores this convention and every reconciliation step — calendar alignment, unit conversion, entity matching — lands on your team instead of the vendor's.

The failure mode is concrete: a source can carry the marketplace product category codes label while differing from what you need on exactly the dimension that matters — the product category table includes furniture_decor, bed_bath_table and housewares. Comparing two sources on that line usually settles the choice faster than any feature matrix.

You rarely have to take a vendor's word for it. 82.4% of the 1,744 datasets Datadory catalogs are free to access, and Brazilian E-Commerce Public Dataset by Olist lets you inspect the real artifact before any budget is committed.

Treat every claim of this attribute as testable:

1. Open Brazilian E-Commerce Public Dataset by Olist and confirm its record — "the product category table includes furniture_decor, bed_bath_table and housewares" — against the files you actually receive.
2. Pin down update cadence in writing. Across this catalog, 22.6% of 1,744 datasets refresh daily and 64 still arrive only through a manual request form, so ask exactly how fresh each release is.
3. Check whether definitions are verified at all. Field definitions are verified for 1495 of 1,744 datasets (85.7%), and any source you license should meet that bar.
4. Price the delivery route before the license. In this catalog bulk download is the most common access method (725 datasets) ahead of official APIs (574), and 379 sources still require scraping — a maintenance cost that lands on you, not the vendor.

See the term applied to real records: apparel-retail data, consumer-electronics data.

Adjacent concepts worth reading next: - product taxonomy - multi-table relational order dump