Data validation for Partners

Ensures a minimum percentage of unique values in the dataset.

Mandates a minimum percentage for filled values.

Makes a field mandatory once filled; triggers an error if left empty afterward.

The value number must not change by more than X amount compared to previous values.

Checks each entry’s data type against its field type (e.g., string, number, date) to ensure integrity and flag mismatches for correction before processing.

Establish a custom rule to validate if the specific field exists and the field value is valid, such as requiring the size string to be ‘S’, ‘M’, or ‘L’; any other value is considered an error.

Requires a minimum of X records for the initial dataset (in specific URL should per the minimum of X records from the total URL inputs)

Validates fluctuations within a +/- X% range.

There are three filter options (All results, Passed, Failed) for dataset test view

This will allow you to reparse the cached data

An option to override a test because the data seems healthy/or it makes sense that the specific dataset does not meet the threshold (note! In case of an override, you will need to write an explanation to the customer)

In case the test failed, click on the “show related records” to see example of the records and then on “View&Edit code” to get to the IDE and start fixing the issues

Reparse:

Reparse involves reprocessing the existing raw data that has already been collected. It applies the parsing logic, rules, or transformations to the data without fetching fresh data from the web. Reparse is useful when changes are needed in data structure, new fields are added to parsing logic, or existing data needs to be restructured or re-extracted.

Recrawl:

Recrawl involves revisiting the source website to collect new or updated data. It fetches fresh data directly from the source to reflect recent changes or additions on the website. Recrawling is useful when the content on the source website changes frequently, or when up-to-date data is critical for analysis or reporting.

Once you finish working on the needed fix, you’ll be able to Reparse or recrawl according to your needs

This will allow you to run the validation tests again if needed

This will allow you to redirect to the IDE in context in case you need to edit the collector and recrawl (e.g in case there are no records at all)

After reviewing the needed data and fixing/ignoring issues, you should click on this button and send the snapshot to the owner for review. The ignored tests should be equipped with a reasoning to explain why you chose to ignore the test

In case not all rejected test was accepted by the owner, the issues will be sent back to you and will be marked with the “Rejected” label for additional fixes and re-sending to the owner for approval