Merge branch 'current' into content/materialized-views/redshift

website/docs/best-practices/materializations/materializations-guide-4-incremental-models.md

@@ -7,7 +7,7 @@ displayText: Materializations best practices
 hoverSnippet: Read this guide to understand the incremental models you can create in dbt.
 ---
 
-So far we’ve looked at tables and views, which map to the traditional objects in the data warehouse. As mentioned earlier, incremental models are a little different. This where we start to deviate from this pattern with more powerful and complex materializations.
+So far we’ve looked at tables and views, which map to the traditional objects in the data warehouse. As mentioned earlier, incremental models are a little different. This is where we start to deviate from this pattern with more powerful and complex materializations.
 
 - 📚 **Incremental models generate tables.** They physically persist the data itself to the warehouse, just piece by piece. What’s different is **how we build that table**.
 - 💅 **Only apply our transformations to rows of data with new or updated information**, this maximizes efficiency.
@@ -53,7 +53,7 @@ where
   updated_at > (select max(updated_at) from {{ this }})
 ```
 
-Let’s break down that `where` clause a bit, because this where the action is with incremental models. Stepping through the code **_right-to-left_** we:
+Let’s break down that `where` clause a bit, because this is where the action is with incremental models. Stepping through the code **_right-to-left_** we:
 
 1. Get our **cutoff.**
    1. Select the `max(updated_at)` timestamp — the **most recent record**
@@ -138,7 +138,7 @@ where
 {% endif %}
 ```
 
-Fantastic! We’ve got a working incremental model. On our first run, when there is no corresponding table in the warehouse, `is_incremental` will evaluate to false and we’ll capture the entire table. On subsequent runs is it will evaluate to true and we’ll apply our filter logic, capturing only the newer data.
+Fantastic! We’ve got a working incremental model. On our first run, when there is no corresponding table in the warehouse, `is_incremental` will evaluate to false and we’ll capture the entire table. On subsequent runs it will evaluate to true and we’ll apply our filter logic, capturing only the newer data.
 
 ### Late arriving facts
 

website/docs/docs/dbt-support.md

@@ -17,7 +17,9 @@ If you're developing on the command line (CLI) and have questions or need some h
 
 ## dbt Cloud support
 
-The global dbt Support team is available to dbt Cloud customers by email or in-product live chat. We want to help you work through implementing and utilizing dbt Cloud at your organization. Have a question you can't find an answer to in [our docs](https://docs.getdbt.com/) or [the Community Forum](https://discourse.getdbt.com/)? Our Support team is here to `dbt help` you!
+The global dbt Support team is available to dbt Cloud customers by [email](mailto:[email protected]) or using the in-product live chat (💬). 
+
+We want to help you work through implementing and utilizing dbt Cloud at your organization. Have a question you can't find an answer to in [our docs](https://docs.getdbt.com/) or [the Community Forum](https://discourse.getdbt.com/)? Our Support team is here to `dbt help` you!
 
 - **Enterprise plans** — Priority [support](#severity-level-for-enterprise-support), options for custom support coverage hours, implementation assistance, dedicated management, and dbt Labs security reviews depending on price point.
 - **Developer and Team plans** — 24x5 support (no service level agreement (SLA); [contact Sales](https://www.getdbt.com/pricing/) for Enterprise plan inquiries).

website/docs/guides/manual-install-qs.md

@@ -16,7 +16,7 @@ When you use dbt Core to work with dbt, you will be editing files locally using
 
 * To use dbt Core, it's important that you know some basics of the Terminal. In particular, you should understand `cd`, `ls` and `pwd` to navigate through the directory structure of your computer easily.
 * Install dbt Core using the [installation instructions](/docs/core/installation-overview) for your operating system.
-* Complete [Setting up (in BigQuery)](/guides/bigquery?step=2) and [Loading data (BigQuery)](/guides/bigquery?step=3).
+* Complete appropriate Setting up and Loading data steps in the Quickstart for dbt Cloud series. For example, for BigQuery, complete [Setting up (in BigQuery)](/guides/bigquery?step=2) and [Loading data (BigQuery)](/guides/bigquery?step=3).
 * [Create a GitHub account](https://github.com/join) if you don't already have one.
 
 ### Create a starter project