Update website/blog/2024-11-27-test-smarter-part-2.md

Co-authored-by: Joel Labes <[email protected]>

website/blog/2024-11-27-test-smarter-part-2.md

@@ -75,7 +75,7 @@ In your intermediate layer, focus on data hygiene and anomaly tests for new colu
 - Intermediate models may perform a first set of joins or aggregations to reduce complexity in a final mart.
     - Add simple anomaly tests to verify the behavior of your sets of joins and aggregations. This may look like:
         - An [accepted_values](/reference/resource-properties/data-tests#accepted_values) test on a newly calculated categorical column.
-        - A [mutually_exclusive_ranges](https://docs.getdbt.com/reference/resource-properties/data-tests#accepted_values) test on two columns whose values behave in relation to one another (ex: asserting age ranges do not overlap).
+        - A [mutually_exclusive_ranges](https://github.com/dbt-labs/dbt-utils#mutually_exclusive_ranges-source) test on two columns whose values behave in relation to one another (ex: asserting age ranges do not overlap).
         - A [not_constant](https://docs.getdbt.com/reference/resource-properties/data-tests#accepted_values) test on a column whose value should be continually changing (ex: page view counts on website analytics).
 - Intermediate models may isolate complex operations.
     - The anomaly tests we list above may suffice here.