Introduction to Exceptions in Turnkey


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Welcome to the world of exceptions! In Turnkey, exceptions are what rules find to identify data of poor quality within your dataset. Let's explore what exceptions are all about:

Note: Currently, Turnkey supports viewing exceptions in the 'PROD' environment only.

Understanding Exceptions

Exceptions are the findings of rules that indicate data quality issues in your dataset. When you navigate to the exceptions tab in Turnkey, you can see all the exceptions that have been identified for each executed rule.

Types of Exceptions

Exceptions can be open or closed. Open exceptions indicate ongoing data quality issues that still exist in the data source. When a rule execution occurs and it cannot find a previously open exception, the exception is marked as closed.

Managing Exceptions

You have the ability to manage exceptions between rule executions. This allows you to use Turnkey as a sort of to-do list, marking exceptions as fixed once they have been addressed. Fixed exceptions are filtered out in subsequent executions, ensuring they no longer appear in the exceptions list.

Additionally, you can snooze exceptions if they are acceptable within a certain timeframe but should be flagged if they persist beyond that. Snoozed exceptions are temporarily ignored during rule executions.

Customizing Exceptions

In some cases, exceptions may not require action or may not be valid. You have the option to mark exceptions as "not an exception" if necessary.

Assigning Exceptions

You can manually assign exceptions to different users within Turnkey. This helps distribute responsibility for resolving exceptions among team members.

 


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