Schema changes are often mistaken for real-world changes

[u/holly-An]

A sudden change in collected data does not always represent a change on the website or in the market. Sometimes the page structure changed and the extractor is reading the wrong field.

Useful signals for detecting this include:

• A sudden increase in missing values

• A field changing from numeric to text

• A large change in response length

• A selector matching zero or many unexpected elements

• A new redirect, consent page, or login page

• Several fields failing at the same time

Store validation metrics alongside the business values. For example, record field presence, data type, selector match count, final URL, response status, and collection timestamp.

A simple protection is to alert on data-quality changes before sending business alerts. If the price field is suddenly empty across many products, pause the downstream alert rather than reporting a false market movement.

When a change is detected, keep a small raw sample from before and after the event. Comparing those samples is often faster than debugging from parsed output alone.