updating links

website/blog/2022-04-19-complex-deduplication.md

@@ -146,7 +146,7 @@ select * from filter_real_diffs
 
 > *What happens in this step? You check your data because you are thorough!*
 
-Good thing dbt has already built this for you. Add a [unique test](/docs/build/data-tests#generic-tests) to your YAML model block for your `grain_id` in this de-duped staging model, and give it a dbt test!
+Good thing dbt has already built this for you. Add a [unique test](/docs/build/data-tests#generic-data-tests) to your YAML model block for your `grain_id` in this de-duped staging model, and give it a dbt test!
 
 ```yaml
 models:

website/blog/2022-10-19-polyglot-dbt-python-dataframes-and-sql.md

@@ -133,9 +133,9 @@ This model tries to parse the raw string value into a Python datetime. When not
 
 #### Testing the result
 
-During the build process, dbt will check if any of the values are null. This is using the built-in [`not_null`](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-tests) test, which will generate and execute SQL in the data platform.
+During the build process, dbt will check if any of the values are null. This is using the built-in [`not_null`](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-data-tests) test, which will generate and execute SQL in the data platform.
 
-Our initial recommendation for testing Python models is to use [generic](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-tests) and [singular](https://docs.getdbt.com/docs/building-a-dbt-project/tests#singular-data-tests) tests.
+Our initial recommendation for testing Python models is to use [generic](https://docs.getdbt.com/docs/building-a-dbt-project/tests#generic-data-tests) and [singular](https://docs.getdbt.com/docs/building-a-dbt-project/tests#singular-data-tests) tests.
 
 ```yaml
 version: 2

website/blog/2023-07-03-data-vault-2-0-with-dbt-cloud.md

@@ -143,7 +143,7 @@ To help you get started, [we have created a template GitHub project](https://git
 
 ### Entity Relation Diagrams (ERDs) and dbt
 
-Data lineage is dbt's strength, but sometimes it's not enough to help you to understand the relationships between Data Vault components like a classic ERD would. There are a few open source packages to visualize the entities in your Data Vault built with dbt. I recommend checking out the [dbterd](https://dbterd.datnguyen.de/1.2/index.html) which turns your [dbt relationship data quality checks](https://docs.getdbt.com/docs/build/tests#generic-tests) into an ERD.
+Data lineage is dbt's strength, but sometimes it's not enough to help you to understand the relationships between Data Vault components like a classic ERD would. There are a few open source packages to visualize the entities in your Data Vault built with dbt. I recommend checking out the [dbterd](https://dbterd.datnguyen.de/1.2/index.html) which turns your [dbt relationship data quality checks](https://docs.getdbt.com/docs/build/tests#generic-data-tests) into an ERD.
 
 ## Summary
 

website/docs/guides/dbt-python-snowpark.md

@@ -1720,7 +1720,7 @@ We test data models for mainly two reasons:
 - Ensure that our source data is clean on ingestion before we start data modeling/transformation (aka avoid garbage in, garbage out problem).
 - Make sure we don’t introduce bugs in the transformation code we wrote (stop ourselves from creating bad joins/fanouts).
 
-Testing in dbt comes in two flavors: [generic](/docs/build/data-tests#generic-tests) and [singular](/docs/build/data-tests#singular-data-tests).
+Testing in dbt comes in two flavors: [generic](/docs/build/data-tests#generic-data-tests) and [singular](/docs/build/data-tests#singular-data-tests).
 
 You define them in a test block (similar to a macro) and once defined, you can reference them by name in your `.yml` files (applying them to models, columns, sources, snapshots, and seeds).
 

website/docs/reference/resource-configs/meta.md

@@ -127,7 +127,7 @@ See [configs and properties](/reference/configs-and-properties) for details.
 
 <TabItem value="tests">
 
-You can't add YAML `meta` configs for [generic tests](/docs/build/data-tests#generic-tests). However, you can add `meta` properties to [singular tests](/docs/build/data-tests#singular-data-tests) using `config()` at the top of the test file. 
+You can't add YAML `meta` configs for [generic tests](/docs/build/data-tests#generic-data-tests). However, you can add `meta` properties to [singular tests](/docs/build/data-tests#singular-data-tests) using `config()` at the top of the test file. 
 
 </TabItem>
 

website/docs/reference/resource-configs/store_failures_as.md

@@ -29,7 +29,7 @@ where 1=0
 
 #### Generic test
 
-[Generic tests](https://docs.getdbt.com/docs/build/tests#generic-tests) in `models/_models.yml` file
+[Generic tests](https://docs.getdbt.com/docs/build/tests#generic-data-tests) in `models/_models.yml` file
 
 ```yaml
 models:

website/docs/reference/resource-properties/data-tests.md

@@ -156,7 +156,7 @@ This feature is not implemented for analyses.
 
 ## Description
 
-The data `tests` property defines assertions about a column, <Term id="table" />, or <Term id="view" />. The property contains a list of [generic tests](/docs/build/data-tests#generic-tests), referenced by name, which can include the four built-in generic tests available in dbt. For example, you can add tests that ensure a column contains no duplicates and zero null values. Any arguments or [configurations](/reference/data-test-configs) passed to those tests should be nested below the test name.
+The data `tests` property defines assertions about a column, <Term id="table" />, or <Term id="view" />. The property contains a list of [generic tests](/docs/build/data-tests#generic-data-tests), referenced by name, which can include the four built-in generic tests available in dbt. For example, you can add tests that ensure a column contains no duplicates and zero null values. Any arguments or [configurations](/reference/data-test-configs) passed to those tests should be nested below the test name.
 
 Once these tests are defined, you can validate their correctness by running `dbt test`.