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mirnawong1 authored Aug 23, 2024
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Expand Up @@ -49,26 +49,26 @@ So far we've been working in new pointing at a staging model to simplify things

```yaml
semantic_models:
- name: locations
description: |
Location dimension table. The grain of the table is one row per location.
model: ref('stg_locations')
entities:
- name: location
type: primary
expr: location_id
dimensions:
- name: location_name
type: categorical
- name: date_trunc('day', opened_at)
type: time
type_params:
time_granularity: day
measures:
- name: average_tax_rate
description: Average tax rate.
expr: tax_rate
agg: avg
- name: locations
description: |
Location dimension table. The grain of the table is one row per location.
model: ref('stg_locations')
entities:
- name: location
type: primary
expr: location_id
dimensions:
- name: location_name
type: categorical
- name: date_trunc('day', opened_at)
type: time
type_params:
time_granularity: day
measures:
- name: average_tax_rate
description: Average tax rate.
expr: tax_rate
agg: avg
```
## Semantic and logical interaction
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Expand Up @@ -10,7 +10,6 @@ pagination_prev: null

The dbt Cloud integrated development environment (IDE) is a single web-based interface for building, testing, running, and version-controlling dbt projects. It compiles dbt code into SQL and executes it directly on your database.

The dbt Cloud IDE offers several [keyboard shortcuts](/docs/cloud/dbt-cloud-ide/keyboard-shortcuts) and [editing features](/docs/cloud/dbt-cloud-ide/ide-user-interface#editing-features) for faster and efficient development and governance:
The dbt Cloud IDE offers several [keyboard shortcuts](/docs/cloud/dbt-cloud-ide/keyboard-shortcuts) and [editing features](/docs/cloud/dbt-cloud-ide/ide-user-interface#editing-features) for faster and efficient development and governance:

- Syntax highlighting for SQL — Makes it easy to distinguish different parts of your code, reducing syntax errors and enhancing readability.
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6 changes: 3 additions & 3 deletions website/docs/docs/cloud/manage-access/audit-log.md
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Expand Up @@ -9,12 +9,12 @@ pagination_prev: "docs/cloud/manage-access/about-user-access"

To review actions performed by people in your organization, dbt provides logs of audited user and system events in real time. The audit log appears as events happen and includes details such as who performed the action, what the action was, and when it was performed. You can use these details to troubleshoot access issues, perform security audits, or analyze specific events.

You must be an **Account Admin** to access the audit log and this feature is only available on Enterprise plans.
You must be an **Account Admin** or an **Account Viewer** to access the audit log and this feature is only available on Enterprise plans.

The dbt Cloud audit log stores all the events that occurred in your organization in real-time, including:

- For events within 90 days, the dbt Cloud audit log has a selectable date range that lists events triggered.
- For events beyond 90 days, **Account Admins** can [export all events](#exporting-logs) by using **Export All**.
- For events beyond 90 days, **Account Admins** and **Account Viewers** can [export all events](#exporting-logs) by using **Export All**.

## Accessing the audit log

Expand Down Expand Up @@ -170,6 +170,6 @@ You can use the audit log to export all historical audit results for security, c

- **For events within 90 days** — dbt Cloud will automatically display the 90-day selectable date range. Select **Export Selection** to download a CSV file of all the events that occurred in your organization within 90 days.

- **For events beyond 90 days** — Select **Export All**. The Account Admin will receive an email link to download a CSV file of all the events that occurred in your organization.
- **For events beyond 90 days** — Select **Export All**. The Account Admin or Account Viewer will receive an email link to download a CSV file of all the events that occurred in your organization.

<Lightbox src="/img/docs/dbt-cloud/dbt-cloud-enterprise/audit-log-section.jpg" width="95%" title="View audit log export options"/>
2 changes: 1 addition & 1 deletion website/docs/docs/cloud/manage-access/external-oauth.md
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Expand Up @@ -172,7 +172,7 @@ Adjust the other settings as needed to meet your organizations configurations in

### Entra ID

You’ll create two different `apps` in the Azure portal &mdash: A resource server and a client app.
You’ll create two different `apps` in the Azure portal &mdash; A resource server and a client app.

:::important

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39 changes: 19 additions & 20 deletions website/docs/docs/cloud/secure/databricks-privatelink.md
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Expand Up @@ -7,6 +7,7 @@ pagination_next: null
---

import SetUpPages from '/snippets/_available-tiers-privatelink.md';
import PrivateLinkSLA from '/snippets/_PrivateLink-SLA.md';

<SetUpPages features={'/snippets/_available-tiers-privatelink.md'}/>

Expand All @@ -15,31 +16,29 @@ The following steps will walk you through the setup of a Databricks AWS PrivateL
## Configure AWS PrivateLink

1. Locate your [Databricks instance name](https://docs.databricks.com/en/workspace/workspace-details.html#workspace-instance-names-urls-and-ids)
- Example: `cust-success.cloud.databricks.com`
2. Add the required information to the following template and submit your AWS PrivateLink request to [dbt Support](https://docs.getdbt.com/docs/dbt-support#dbt-cloud-support):
```
Subject: New AWS Multi-Tenant PrivateLink Request
- Type: Databricks
- Databricks instance name:
- Databricks cluster AWS Region (e.g., us-east-1, eu-west-2):
- dbt Cloud multi-tenant environment (US, EMEA, AU):
```

import PrivateLinkSLA from '/snippets/_PrivateLink-SLA.md';
- Example: `cust-success.cloud.databricks.com`

<PrivateLinkSLA />
1. Add the required information to the following template and submit your AWS PrivateLink request to [dbt Support](https://docs.getdbt.com/docs/dbt-support#dbt-cloud-support):
```
Subject: New AWS Multi-Tenant PrivateLink Request
- Type: Databricks
- Databricks instance name:
- Databricks cluster AWS Region (e.g., us-east-1, eu-west-2):
- dbt Cloud multi-tenant environment (US, EMEA, AU):
```
<PrivateLinkSLA />
3. Once dbt Cloud support has notified you that setup is complete, [register the VPC endpoint in Databricks](https://docs.databricks.com/administration-guide/cloud-configurations/aws/privatelink.html#step-3-register-privatelink-objects-and-attach-them-to-a-workspace) and attach it to the workspace:
- [Register your VPC endpoint](https://docs.databricks.com/en/security/network/classic/vpc-endpoints.html) &mdash; Register the VPC endpoint using the VPC endpoint ID provided by dbt Support.
- [Create a Private Access Settings object](https://docs.databricks.com/en/security/network/classic/private-access-settings.html) &mdash; Create a Private Access Settings (PAS) object with your desired public access settings, and setting Private Access Level to **Endpoint**. Choose the registered endpoint created in the previous step.
- [Create or update your workspace](https://docs.databricks.com/en/security/network/classic/privatelink.html#step-3d-create-or-update-the-workspace-front-end-back-end-or-both) &mdash; Create a workspace, or update your an existing workspace. Under **Advanced configurations → Private Link** choose the private access settings object created in the previous step.
1. Once dbt Cloud support has notified you that setup is complete, [register the VPC endpoint in Databricks](https://docs.databricks.com/administration-guide/cloud-configurations/aws/privatelink.html#step-3-register-privatelink-objects-and-attach-them-to-a-workspace) and attach it to the workspace:
- [Register your VPC endpoint](https://docs.databricks.com/en/security/network/classic/vpc-endpoints.html) &mdash; Register the VPC endpoint using the VPC endpoint ID provided by dbt Support.
- [Create a Private Access Settings object](https://docs.databricks.com/en/security/network/classic/private-access-settings.html) &mdash; Create a Private Access Settings (PAS) object with your desired public access settings, and setting Private Access Level to **Endpoint**. Choose the registered endpoint created in the previous step.
- [Create or update your workspace](https://docs.databricks.com/en/security/network/classic/privatelink.html#step-3d-create-or-update-the-workspace-front-end-back-end-or-both) &mdash; Create a workspace, or update your an existing workspace. Under **Advanced configurations → Private Link** choose the private access settings object created in the previous step.
:::note Warning
If using an existing Databricks workspace, all workloads running in the workspace will need to be stopped to enable Private Link! Workloads also cannot be started for another 20 minutes after making changes. From the [Databricks documentation](https://docs.databricks.com/en/security/network/classic/privatelink.html#step-3d-create-or-update-the-workspace-front-end-back-end-or-both):
:::warning
If using an existing Databricks workspace, all workloads running in the workspace need to be stopped to enable Private Link. Workloads also can't be started for another 20 minutes after making changes. From the [Databricks documentation](https://docs.databricks.com/en/security/network/classic/privatelink.html#step-3d-create-or-update-the-workspace-front-end-back-end-or-both):
>After creating (or updating) a workspace, wait until it’s available for using or creating clusters. The workspace status stays at status RUNNING and the VPC change happens immediately. However, you cannot use or create clusters for another 20 minutes. If you create or use clusters before this time interval elapses, clusters do not launch successfully, fail, or could cause other unexpected behavior.
"After creating (or updating) a workspace, wait until it’s available for using or creating clusters. The workspace status stays at status RUNNING and the VPC change happens immediately. However, you cannot use or create clusters for another 20 minutes. If you create or use clusters before this time interval elapses, clusters do not launch successfully, fail, or could cause other unexpected behavior."
:::
:::
## Configure Azure Private Link
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2 changes: 1 addition & 1 deletion website/docs/docs/use-dbt-semantic-layer/exports.md
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Expand Up @@ -54,7 +54,7 @@ Before you're able to run exports in development or production, you'll need to m

There are two ways to run an export:

- [Run exports in development](#exports-in-development) using the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation) to test the output before production (dbt Cloud IDE isn't supported yet).
- [Run exports in development](#exports-in-development) using the [dbt Cloud CLI](/docs/cloud/cloud-cli-installation) to test the output before production (You can configure exports in the dbt Cloud IDE, however running them directly in the IDE isn't supported yet).
- [Run exports in production](#exports-in-production) using the [dbt Cloud job scheduler](/docs/deploy/job-scheduler) to write these queries within your data platform.

## Exports in development
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Expand Up @@ -17,18 +17,18 @@ unit_tests:
unit_tests:
- name: test_is_valid_email_address
model: my_model
versions:
include:
- 2
versions:
include:
- 2
...

# my test_is_valid_email_address unit test will run on all versions EXCEPT 1 of my_model
unit_tests:
- name: test_is_valid_email_address
model: my_model
versions:
exclude:
- 1
versions:
include:
- 1
...

```
```
9 changes: 8 additions & 1 deletion website/docs/terms/model.md
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Expand Up @@ -6,4 +6,11 @@ displayText: model
hoverSnippet: A model is an essential building block of the DAG
---

A model is an essential building block of the DAG that lives in a single file and contains logic that transforms data. This logic can be expressed as a SQL `select` statement or a Python dataframe operation. Models can be materialized in the warehouse in different ways &mdash; most of these materializations require models to be built in the warehouse.
A model is an essential building block of the DAG that lives in a single file and contains logic that transforms data. This logic can be expressed as a SQL `select` statement or a Python dataframe operation. Models can be materialized in the warehouse in different ways &mdash; most of these [materialization](/terms/materialization) require models to be built in the warehouse.

For more information, refer to:

* [About dbt models](/docs/build/models)
* [Quickstart guides](/guides?tags=Quickstart)
* [Model properties](/reference/model-properties)
* [Materializations](/reference/resource-configs/materialized)
2 changes: 1 addition & 1 deletion website/snippets/_adapters-trusted.md
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Expand Up @@ -15,7 +15,7 @@
<Card
title="Athena"
body="<ul><li><a href='/docs/cloud/connect-data-platform/connect-amazon-athena'>Set up in dbt Cloud (beta) </a><br /></li><li><a href='/docs/core/connect-data-platform/athena-setup'>Install with dbt Core </a> </li> </ul><br /><br /><a href=https://badge.fury.io/py/dbt-athena-community><img src=https://badge.fury.io/py/dbt-athena-community.svg/></a>"
pills='["dbt Core"]'
pills='["dbt Cloud", "dbt Core"]'
icon="athena"/>

<Card
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4 changes: 2 additions & 2 deletions website/snippets/_enterprise-permissions-table.md
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Expand Up @@ -19,6 +19,7 @@ Account roles enable you to manage the dbt Cloud account and manage the account
| Audit logs | R | | | | R | R |
| Auth provider | W | | | | W | R |
| Billing | W | W | | | | R |
| Connections | W | | | W | | |
| Groups | W | | | R | W | R |
| Invitations | W | | | W | W | R |
| IP restrictions | W | | | | W | R |
Expand All @@ -34,7 +35,6 @@ Account roles enable you to manage the dbt Cloud account and manage the account

|Project-level permission | Account Admin | Billing admin | Project creator | Security admin | Viewer |
|:-------------------------|:-------------:|:-------------:|:---------------:|:--------------:|:------:|
| Data platform connections | W | | W | | R |
| Environment credentials (deployment) | W | | W | | R |
| Custom env. variables | W | | W | | R |
| Data platform configurations | W | | W | | R |
Expand All @@ -61,6 +61,7 @@ The project roles enable you to work within the projects in various capacities.
| Account settings | R | | R | | R | | | | | | | R | |
| Auth provider | | | | | | | | | | | | | |
| Billing | | | | | | | | | | | | | |
| Connections | R | R | R | R | R | R | | | | | R | R | |
| Groups | R | | R | R | R | | | | | | R | R | |
| Invitations | W | R | R | R | R | R | | R | | | R | R | |
| Licenses | W | R | R | R | R | R | | R | | | | R | |
Expand All @@ -74,7 +75,6 @@ The project roles enable you to work within the projects in various capacities.

|Project-level permission | Admin | Analyst | Database admin | Developer | Git Admin | Job admin | Job runner | Job viewer | Metadata <br></br> (Discovery API only) | Semantic Layer | Stakeholder | Team admin | Webhook |
|--------------------------|:-----:|:-------:|:--------------:|:---------:|:---------:|:---------:|:-----------:|:-----------:|:--------:|:--------------:|:-----------:|:----------:|:-------:|
| Data platform connections | W | R | W | R | R | R | | | | | R | R | |
| Environment credentials (deployment) | W | W | W | W | R | W | | | | | R | R | |
| Custom env. variables | W | W | W | W | W | W | | R | | | R | W | |
| Data platform configurations | W | W | W | W | R | W | | | | | R | R | |
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