Update build-metrics-intro.md (#3867)

add clarification that postgres supported in metricflow but not dbt
cloud yet per [slack
thread](https://getdbt.slack.com/archives/C046L0VTVR6/p1691092050990009?thread_ts=1691089665.187629&cid=C046L0VTVR6)

- Use MetricFlow with Snowflake, BigQuery, Databricks, Postgres (CLI
only), or Redshift. (dbt Cloud Postgres support coming soon)

## What are you changing in this pull request and why?
<!---
Describe your changes and why you're making them. If linked to an open
issue or a pull request on dbt Core, then link to them here! 

To learn more about the writing conventions used in the dbt Labs docs,
see the [Content style
guide](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/content-style-guide.md).
-->

## Checklist
<!--
Uncomment if you're publishing docs for a prerelease version of dbt
(delete if not applicable):
- [ ] Add versioning components, as described in [Versioning
Docs](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/single-sourcing-content.md#versioning-entire-pages)
- [ ] Add a note to the prerelease version [Migration
Guide](https://github.com/dbt-labs/docs.getdbt.com/tree/current/website/docs/guides/migration/versions)
-->
- [ ] Review the [Content style
guide](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/content-style-guide.md)
and [About
versioning](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/single-sourcing-content.md#adding-a-new-version)
so my content adheres to these guidelines.
- [ ] Add a checklist item for anything that needs to happen before this
PR is merged, such as "needs technical review" or "change base branch."

Adding new pages (delete if not applicable):
- [ ] Add page to `website/sidebars.js`
- [ ] Provide a unique filename for the new page

Removing or renaming existing pages (delete if not applicable):
- [ ] Remove page from `website/sidebars.js`
- [ ] Add an entry `website/static/_redirects`
- [ ] [Ran link
testing](https://github.com/dbt-labs/docs.getdbt.com#running-the-cypress-tests-locally)
to update the links that point to the deleted page

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

@@ -21,7 +21,7 @@ Before you start, consider the following guidelines:
 
 - Define metrics in YAML and query them using these [new metric specifications](https://github.com/dbt-labs/dbt-core/discussions/7456).
 - You must be on dbt v1.6 or higher to use MetricFlow. [Upgrade your dbt Cloud version](/docs/dbt-versions/upgrade-core-in-cloud) to get started.
-- Use MetricFlow with Snowflake, Postgres, BigQuery, Databricks, or Redshift.
+- Use MetricFlow with Snowflake, BigQuery, Databricks, Postgres (CLI only), or Redshift. (dbt Cloud Postgres support coming soon)
 - Unlock insights and query your metrics using the [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) and its diverse range of [available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations).
 
 

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

@@ -13,9 +13,9 @@ The keys for metrics definitions are:
 | Component | Description | Type |
 | --------- | ----------- | ---- |
 | `name` | Provide the reference name for the metric. This name must be unique amongst all metrics.   | Required |
-| `type` | Define the type of metric, which can be a measure (`simple`) or ratio (`ratio`)).  | Optional |
+| `type` | Define the type of metric, which can be a measure (`simple`) or ratio (`ratio`)).  | Required |
 | `type_params` | Additional parameters used to configure metrics. `type_params` are different for each metric type. | Required |
-| `filter` | For any type of metric, you may optionally include a filter string, which applies a filter for a dimension, entity or time dimension when computing the metric. You can think of this as your WHERE clause.   | Optional |
+| `filter` | For any type of metric, you may optionally include a filter string, which applies a filter for a dimension, entity, or time dimension when computing the metric. You can think of this as your WHERE clause.   | Optional |
 |  `meta` | Additional metadata you want to add to your metric. |
 
 
@@ -38,7 +38,7 @@ metrics:
 This page explains the different supported metric types you can add to your dbt project. 
 <!--
 - [Cumulative](#cumulative-metrics) — Cumulative metrics aggregate a measure over a given window.
-- [Derived](#derived-metrics) — An expression of other metrics, which allows you to do calculation on top of metrics.
+- [Derived](#derived-metrics) — An expression of other metrics, which allows you to do calculations on top of metrics.
 - [Expression](#expression-metrics) — Allow measures to be modified using a SQL expression.
 - [Measure proxy](#measure-proxy-metrics) — Metrics that refer directly to one measure.
 - [Ratio](#ratio-metrics) — Create a ratio out of two measures. 
@@ -148,7 +148,8 @@ metrics:
 ```
 
 ## Filters
-Filter are configured using jinja templating. Use the following syntax to refrence entites, dimensions and time dimensions in filters:
+
+A filter is configured using Jinja templating. Use the following syntax to reference entities, dimensions, and time dimensions in filters:
 ```yaml
 filter: |
   {{ Entity('entity_name') }} 
@@ -163,7 +164,7 @@ You can set more metadata for your metrics, which can be used by other tools lat
 
 - **Description** &mdash;  Write a detailed description of the metric.
 
-<!--Provide a detailed description of the metric. This description is surfaced in the main “definition” section of the metric page using rich Markdown formatting in the Transform UI. [this includes transform and not sure how this looks in core and cloud]-->
+<!--Provide a detailed description of the metric. This description surfaced in the main “definition” section of the metric page using rich Markdown formatting in the Transform UI. [this includes transform and not sure how this looks in core and cloud]-->
 
 
 ## Related docs

website/docs/docs/build/sl-getting-started.md

@@ -29,7 +29,7 @@ To fully experience the power of a universal dbt Semantic Layer, take the follow
 
 - Have an understanding of key concepts in [MetricFlow](/docs/build/about-metricflow), which powers the revamped dbt Semantic Layer.
 - Have both your production and development environments running dbt version 1.6 or higher. Refer to [upgrade in dbt Cloud](/docs/dbt-versions/upgrade-core-in-cloud) for more info.
-- Use Snowflake, BigQuery, Databricks, or Redshift data platform
+- Use MetricFlow with Snowflake, BigQuery, Databricks, Postgres (CLI only), or Redshift. (dbt Cloud Postgres support coming soon)
 - A successful run in the environment where your Semantic Layer is configured
 - To query with dbt Cloud:
   * Have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America (Other regions coming soon)

website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md

@@ -23,7 +23,7 @@ import TestQuery from '/snippets/_sl-test-and-query-metrics.md';
 
 The dbt Semantic Layer, powered by [MetricFlow](/docs/build/about-metricflow), simplifies defining and using critical business metrics. It centralizes metric definitions, eliminates duplicate coding, and ensures consistent self-service access to metrics in downstream tools. 
 
-MetricFlow is a powerful component within the dbt Semantic Layer that helps users define and manage company metrics efficiently. It provides flexible abstractions and SQL query generation, and also allows data consumers to retrieve metric datasets quickly and easily from a data platform.
+MetricFlow is a powerful component within the dbt Semantic Layer that helps users define and manage company metrics efficiently. It provides flexible abstractions and SQL query generation and also allows data consumers to retrieve metric datasets quickly and easily from a data platform.
 
 Use this guide to fully experience the power of a universal dbt Semantic Layer. Here are the following steps you'll take:
 

website/snippets/_v2-sl-prerequisites.md

@@ -3,11 +3,11 @@
 
 To use the Semantic Layer, you must:
 
-- Have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America
-- Have both your production and development environments running dbt version 1.6 or higher 
-- Use Snowflake, BigQuery, Databricks, and Redshift data platform
+- Have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America.
+- Have both your production and development environments running dbt version 1.6 or higher.
+- Use Snowflake, BigQuery, Databricks, or Redshift (dbt Cloud Postgres support coming soon).
 -  Create a successful run in the environment where you configure the Semantic Layer. <br/>
-  **Note:** Semantic Layer currently supports Deployment environment. (_development experience coming soon_)
+  **Note:** Semantic Layer currently supports the Deployment environment. (_development experience coming soon_)
 - Install the [MetricFlow CLI](/docs/build/metricflow-cli). After installing the package, make sure you run at least one model.
 - Set up the [Semantic Layer API](/docs/dbt-cloud-apis/sl-api-overview) in the integrated tool to import metric definitions. <br /> 
 **Note:** Developer accounts can only query data manually using the [MetricFlow CLI](/docs/build/metricflow-cli) and SQL. To dynamically query metrics using external tools, you must have a dbt Cloud Team or Enterprise account with access to the Semantic Layer API.<br />