If you run a website, you are already sitting on structured data: page metadata, taxonomy, internal linking, content performance, and on-site search behavior. Most of it never gets extracted.
Inventory what already exists
List every place structured information already lives, page titles and descriptions, category and tag taxonomy, publish dates, internal link relationships, and analytics events. This is your raw material before you collect anything new.
Export from the source of truth
For flat-file and JSON-driven sites, this is often a direct file export. For database-backed sites, write a query that pulls the fields you need rather than scraping your own rendered HTML.
Normalize into a flat structure
Website content is usually nested. A dataset needs a flatter, tabular shape, one row per page or per entity, with consistent column names across the whole export.
Add the signals that make it valuable
Raw content fields are a start. The dataset becomes more useful once you add derived signals, word count, publish-to-update gap, internal link count, or category depth.
Decide what stays internal
Not everything on your site belongs in a dataset you sell or publish. Strip anything sensitive, then package the rest as CSV or JSON for the audience that wants it.
A site with years of consistent structure is a dataset waiting to be exported. The work is mostly extraction and normalization, not new data collection.