general

Data Freshness

Data freshness measures how recently scraped data was collected relative to the actual source, a critical metric for price monitoring, news aggregation, and inventory tracking.

Scraped data has a shelf life. A product price scraped 24 hours ago may no longer reflect the current price; a flight fare scraped 6 hours ago may have changed. For use cases where currency matters — competitive pricing, live inventory, news alerts — data freshness is as important as accuracy.

Freshness is typically tracked by recording a `scraped_at` timestamp alongside each record and measuring the lag between when the source updated and when the scraper captured the change. SLA-driven scraping systems define freshness requirements per data type (e.g., prices must be at most 30 minutes old) and configure crawl schedules accordingly.

Event-driven scraping improves freshness compared to fixed schedules: instead of crawling every N hours, the system triggers a re-scrape whenever a change signal is detected (a product's last-modified header changes, a sitemap entry's `<lastmod>` updates, or a webhook fires from the source platform).

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    Data Freshness — Web Scraping Glossary | AlterLab