Merge pull request #180 from dbt-labs/repo-sync

REPO SYNC - Public to Private

website/docs/docs/build/cumulative-metrics.md

@@ -19,9 +19,9 @@ metrics:
     label: The value that will be displayed in downstream tools # Required
     type_params: # Required
       measure: the measure you are referencing # Required
-      window: the accumulation window i.e 1 month, 7 days, 1 year. # Optional. Cannot be used with window
+      window: the accumulation window i.e 1 month, 7 days, 1 year. # Optional. Cannot be used with grain_to_date
       grain_to_date: sets the accumulation grain, such as month will accumulate data for one month, then restart at the beginning of the next. 
-      # Optional. Can not be used with grain_to_date. 
+      # Optional. Can not be used with window. 
 
 
 ```

website/docs/docs/build/measures.md

@@ -12,7 +12,7 @@ Measures are aggregations performed on columns in your model. They can be used a
 | --- | --- | --- |
 | [`name`](#name) | Provide a name for the measure, which must be unique and can't be repeated across all semantic models in your dbt project. | Required |
 | [`description`](#description) | Describes the calculated measure. | Optional |
-| [`agg`](#aggregation) | dbt supports the following aggregations: `sum`, `max`, `min`, `count_distinct`, and `sum_boolean`. | Required |
+| [`agg`](#aggregation) | dbt supports aggregations such as `sum`, `min`, `max`, and more. Refer to [Aggregation](/docs/build/measures#aggregation) for the full list of supported aggregation types. | Required |
 | [`expr`](#expr) | You can either reference an existing column in the table or use a SQL expression to create or derive a new one. | Optional |
 | [`non_additive_dimension`](#non-additive-dimensions) | Non-additive dimensions can be specified for measures that cannot be aggregated over certain dimensions, such as bank account balances, to avoid producing incorrect results. | Optional |
 | `agg_params` | specific aggregation properties such as a percentile. | Optional |

website/docs/docs/deploy/deploy-environments.md

@@ -34,6 +34,8 @@ import ExpBeta from '/snippets/_explorer-beta-banner.md';
 
 <ExpBeta/>
 
+<Lightbox src="/img/docs/dbt-cloud/using-dbt-cloud/prod-settings.jpg" width="70%" title="Set your production environment as the default environment in your Environment Settings"/>
+
 In dbt Cloud, each project can have one designated deployment environment, which serves as its production environment. This production environment is _essential_ for using features like dbt Explorer and cross-project references. It acts as the source of truth for the project's production state in dbt Cloud.
 
 ### Semantic Layer

website/docs/guides/orchestration/custom-cicd-pipelines/4-dbt-cloud-job-on-pr.md

@@ -89,7 +89,7 @@ As noted above, when the PR job runs it will create a new schema based on the PR
 
 Add this as a macro to your project. It takes 2 arguments that lets you control which schema get dropped:
   - `age_in_days`: The number of days since the schema was last altered before it should be dropped (default 10 days)
-  - `databse_to_clean`: The name of the database to remove schemas from
+  - `database_to_clean`: The name of the database to remove schemas from
 
 ```sql
 {# 
@@ -128,4 +128,4 @@ Add this as a macro to your project. It takes 2 arguments that lets you control
 
 This macro goes into a dbt Cloud job that is run on a schedule. The command will look like this (text below for copy/paste):
 ![dbt Cloud job showing the run operation command for the cleanup macro](/img/guides/orchestration/custom-cicd-pipelines/dbt-macro-cleanup-pr.png)
-`dbt run-operation pr_schema_cleanup --args "{ 'database_to_clean': 'development','age_in_days':15}"`
+`dbt run-operation pr_schema_cleanup --args "{ 'database_to_clean': 'development','age_in_days':15}"`