Dataset Discovery
Datachecks automatically detects databases and tables, allowing you to apply inclusion or exclusion patterns to control which ones are monitored.
You can control which tables are included or excluded from profiling and monitoring by using the Table Inclusion List and Table Exclusion List. All datasets matching a specified pattern will be included or excluded accordingly. These fields support flexible pattern-based matching using the following syntax:
Table Filtering Patterns
| Pattern Type | Description | Example Matches |
|---|---|---|
% Wildcard | Matches any sequence of characters | %user → admin_user, active_user |
_ Wildcard | Matches exactly one character | customer__ → customer01, customerAB |
* Wildcard | Matches zero or more characters | user*data → user_metadata, user_salesdata |
| Escaped Wildcards | Use \ to match literal wildcard characters | north\_% → north_star, north_end |
| Exact Match | Matches only the exact table name | retailorders → matches only retailorders |
Inclusion patterns take precedence over exclusion patterns. If a table matches both inclusion and exclusion lists, it will be included.
Additionally, you can now choose to enable or disable view scanning when setting up a datasource.
This provides greater control over whether database views should be included during dataset discovery and profiling.
Updated 11 days ago