From 080ba7785e5bc1a0086a9ffc5e92c4694029dfc1 Mon Sep 17 00:00:00 2001 From: Mirna Wong <89008547+mirnawong1@users.noreply.github.com> Date: Mon, 12 Aug 2024 22:49:20 +0100 Subject: [PATCH] model query and auto-exposures beta (#5896) this pr adds model query history and auto exposures (beta) to the doca site for the broader beta cycle. [docs project](https://www.notion.so/dbtlabs/BI-auto-exposures-model-query-history-embeddable-tile-00b9411c36e748f09d16ede9136fc7ec) outstanding questions: - is data health tile enterprise only? or team + enterprise? - is the beta call out (for feedback to to take part bit) correct? [ ] PM review required [x ] Docs review optional since beta --------- Co-authored-by: nataliefiann <120089939+nataliefiann@users.noreply.github.com> Co-authored-by: Leona B. Campbell <3880403+runleonarun@users.noreply.github.com> --- website/docs/docs/build/exposures.md | 2 +- .../configure-auto-exposures.md | 75 +++++++ .../docs/docs/cloud-integrations/overview.md | 16 +- .../docs/docs/collaborate/auto-exposures.md | 23 ++ website/docs/docs/collaborate/data-tile.md | 209 ++++++++++++++++++ .../docs/collaborate/dbt-explorer-faqs.md | 2 +- .../docs/docs/collaborate/explore-projects.md | 30 ++- .../docs/collaborate/model-query-history.md | 100 +++++++++ .../docs/docs/dbt-cloud-apis/discovery-api.md | 5 +- .../discovery-use-cases-and-examples.md | 2 +- .../docs/deploy/dashboard-status-tiles.md | 102 --------- .../docs/docs/deploy/deployment-overview.md | 8 +- website/docs/docs/deploy/monitor-jobs.md | 3 +- ...oductionize-your-dbt-databricks-project.md | 2 +- website/sidebars.js | 17 +- website/snippets/_auto-exposures-view.md | 20 ++ .../auto-exposures/cloud-add-integration.jpg | Bin 0 -> 314353 bytes .../cloud-integration-details.jpg | Bin 0 -> 305394 bytes 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create mode 100644 website/static/img/docs/collaborate/dbt-explorer/data-tile-example.jpg create mode 100644 website/static/img/docs/collaborate/dbt-explorer/data-tile-exposures.jpg create mode 100644 website/static/img/docs/collaborate/dbt-explorer/data-tile-iframe.jpg create mode 100644 website/static/img/docs/collaborate/dbt-explorer/data-tile-pass.jpg create mode 100644 website/static/img/docs/collaborate/dbt-explorer/data-tile-setup.jpg create mode 100644 website/static/img/docs/collaborate/dbt-explorer/data-tile-stale.jpg create mode 100644 website/static/img/docs/collaborate/dbt-explorer/model-query-credentials.jpg create mode 100644 website/static/img/docs/collaborate/dbt-explorer/model-query-lenses.jpg create mode 100644 website/static/img/docs/collaborate/dbt-explorer/model-query-list.jpg create mode 100644 website/static/img/docs/collaborate/dbt-explorer/model-query-queried-models.jpg create mode 100644 website/static/img/docs/collaborate/dbt-explorer/model-query-usage-queries.jpg delete mode 100644 website/static/img/docs/dbt-cloud/discovery-api/data-freshness-metadata.jpg diff --git a/website/docs/docs/build/exposures.md b/website/docs/docs/build/exposures.md index 4f027fa7d29..1a85d5fb415 100644 --- a/website/docs/docs/build/exposures.md +++ b/website/docs/docs/build/exposures.md @@ -78,4 +78,4 @@ When we generate the dbt Explorer site, you'll see the exposure appear: * [Exposure properties](/reference/exposure-properties) * [`exposure:` selection method](/reference/node-selection/methods#the-exposure-method) -* [Dashboard status tiles](/docs/deploy/dashboard-status-tiles) +* [Data health tiles](/docs/collaborate/data-tile) diff --git a/website/docs/docs/cloud-integrations/configure-auto-exposures.md b/website/docs/docs/cloud-integrations/configure-auto-exposures.md new file mode 100644 index 00000000000..6314a0eb213 --- /dev/null +++ b/website/docs/docs/cloud-integrations/configure-auto-exposures.md @@ -0,0 +1,75 @@ +--- +title: "Auto-exposures" +id: "configure-auto-exposures" +sidebar_label: "Configure auto-exposures" +description: "Import and auto-generate exposures from dashboards and understand how models are used in downstream tools for a richer lineage." +image: /img/docs/cloud-integrations/auto-exposures/explorer-lineage2.jpg +--- + +# Configure auto-exposures + +As a data team, it’s critical that you have context into the downstream use cases and users of your data products. [Auto-exposures](/docs/collaborate/auto-exposures) integrates natively with Tableau and [auto-generates downstream lineage](/docs/collaborate/auto-exposures#view-auto-exposures-in-dbt-explorer) in dbt Explorer for a richer experience. +:::info Available in beta +Auto-exposures are currently available in beta to a limited group of users and are gradually being rolled out. If you're interested in gaining access or learning more, stay tuned for updates! +::: +Auto-exposures help data teams optimize their efficiency and ensure data quality by: + +- Helping users understand how their models are used in downstream analytics tools to inform investments and reduce incidents — ultimately building trust and confidence in data products. +- Importing and auto-generating exposures based on Tableau dashboards, with user-defined curation. +- Enabling the active exposure work to run models based on when exposures are updated or need to be updated, improving timeliness and reducing costs. + +## Prerequisites + +To access the features, you should meet the following: + +1. You have a dbt Cloud account on the [Enterprise plan](https://www.getdbt.com/pricing/). +2. You have set up a [production](/docs/deploy/deploy-environments#set-as-production-environment) deployment environment for each project you want to explore, with at least one successful job run. +3. You have [admin permissions](/docs/cloud/manage-access/enterprise-permissions) in dbt Cloud to edit project settings or production environment settings +4. Use Tableau as your BI tool and can enable metadata permissions or work with an admin to do so. Compatible with Tableau Cloud or Tableau Server with the Metadata API enabled. + +## Set up in Tableau + +This section of the document explains the steps you need to set up the auto-exposures integration with Tableau. Once you've set this up in Tableau and dbt Cloud, you can view the [auto-exposures](/docs/collaborate/auto-exposures#view-auto-exposures-in-dbt-explorer) in dbt Explorer. + +To set up [personal access tokens (PATs)](/docs/dbt-cloud-apis/user-tokens#using-the-new-personal-access-tokens) needed for auto exposures, ask a site admin to configure it for the account. + +1. Ensure you or a site admin enables PATs for the account in Tableau. + + +2. Create a PAT that you can add to dbt Cloud to pull in Tableau metadata for auto exposures. + + +3. Copy the **Secret** and the **Token name** and enter them in dbt Cloud. The secret is only displayed once, so store it in a safe location (like a password manager). + + +4. Copy the **Server URL** and **Sitename**. You can find these in the URL while logged into Tableau. + + + For example, if the full URL is: `10az.online.tableau.com/#/site/dbtlabspartner/explore`: + - The **Server URL** is the first part of the URL, in this case: `10az.online.tableau.com` + - The **Sitename** is right after the `site` in the URL, in this case: `dbtlabspartner` + +5. You should now be ready to set up auto-exposures in dbt Cloud after copying the following items, which you'll need during the dbt Cloud setup: ServerURL, Sitename, Token name, and Secret. + +## Set up in dbt Cloud + +1. In dbt Cloud, navigate to the project you want to add the auto-exposures to and then select **Settings**. +2. Under the **Exposures** section, select **Add integration** to add the Tableau connection. + +3. Enter the details for the exposure connection you collected from Tableau in the [previous step](#set-up-in-tableau) and click **Continue**. Note that all fields are case-sensitive. + +4. Select the collections you want to include for auto exposures. + + dbt Cloud automatically imports and syncs any workbook within the selected collections. New additions to the collections will be added to the lineage in dbt Cloud during the next automatic sync (usually once per day). + +5. Click **Save**. dbt Cloud imports everything in this collection and you can continue to view them in Explorer using the next steps. + +For more information on how to view and use auto-exposures, refer to [View auto-exposures from dbt Explorer](/docs/collaborate/auto-exposures) page. + + + +## Refresh auto-exposures in jobs + +:::info Coming soon +Soon, you’ll also be able to use auto-exposures trigger refresh of the data used in your Tableau dashboards from within dbt Cloud. Stay tuned for more on this soon! +::: diff --git a/website/docs/docs/cloud-integrations/overview.md b/website/docs/docs/cloud-integrations/overview.md index e0adfe72303..d925e3e52a7 100644 --- a/website/docs/docs/cloud-integrations/overview.md +++ b/website/docs/docs/cloud-integrations/overview.md @@ -2,15 +2,21 @@ title: "About dbt Cloud integrations" sidebar_label: "About dbt Cloud integrations" pagination_prev: null -pagination_next: "docs/cloud-integrations/snowflake-native-app" +pagination_next: "docs/cloud-integrations/configure-auto-exposures" +hide_table_of_contents: true --- Many data applications integrate with dbt Cloud, enabling you to leverage the power of dbt for a variety of use cases and workflows. - ## Integrations with dbt -
+
+ + -
\ No newline at end of file +
diff --git a/website/docs/docs/collaborate/auto-exposures.md b/website/docs/docs/collaborate/auto-exposures.md new file mode 100644 index 00000000000..7e4b4531876 --- /dev/null +++ b/website/docs/docs/collaborate/auto-exposures.md @@ -0,0 +1,23 @@ +--- +title: "Auto-exposures" +sidebar_label: "Auto-exposures" +description: "Import and auto-generate exposures from dashboards and understand how models are used in downstream tools for a richer lineage." +pagination_prev: null +pagination_next: "docs/collaborate/data-tile" +image: /img/docs/cloud-integrations/auto-exposures/explorer-lineage.jpg +--- + +# Auto-exposures + +As a data team, it’s critical that you have context into the downstream use cases and users of your data products. Auto-exposures integrates natively with Tableau (Power BI coming soon) and auto-generates downstream lineage in dbt Explorer for a richer experience. +:::info Available in beta +Auto-exposures are currently available in beta to a limited group of users and are gradually being rolled out. If you're interested in gaining access or learning more, stay tuned for updates! +::: + +Auto-exposures helps users understand how their models are used in downstream analytics tools to inform investments and reduce incidents — ultimately building trust and confidence in data products. It imports and auto-generates exposures based on Tableau dashboards, with user-defined curation. + +For more information on how to set up auto-exposures, prerequisites, and more — refer to [configure auto-exposures in Tableau and dbt Cloud](/docs/cloud-integrations/configure-auto-exposures). + +import ViewExposures from '/snippets/_auto-exposures-view.md'; + + diff --git a/website/docs/docs/collaborate/data-tile.md b/website/docs/docs/collaborate/data-tile.md new file mode 100644 index 00000000000..c5e9a14b556 --- /dev/null +++ b/website/docs/docs/collaborate/data-tile.md @@ -0,0 +1,209 @@ +--- +title: "Data health tile" +id: "data-tile" +sidebar_label: "Data health tile" +description: "Embed data health tiles in your dashboards to distill trust signals for data consumers." +image: /img/docs/collaborate/dbt-explorer/data-tile-pass.jpg +--- + +# Embed data health tile in dashboards + +With data health tiles, stakeholders will get an at-a-glance confirmation on whether the data they’re looking at is stale or degraded. This trust signal allows teams to immediately go back into Explorer to see more details and investigate issues. +:::info Available in beta +Data health tiles are currently available in beta to a limited group of users and are gradually being rolled out. If you're interested in gaining access or learning more, stay tuned for updates! +::: +The data health tile: + +- Distills trust signals for data consumers. +- Deep links you into dbt Explorer where you can further dive into upstream data issues. +- Provides richer information and makes it easier to debug. +- Revamps the existing, [job-based tiles](#job-based-data-health). + + + +## Prerequisites + +- You must have a dbt Cloud account on a [Team or Enterprise plan](https://www.getdbt.com/pricing/). +- You must be an account admin to set up [service tokens](/docs/dbt-cloud-apis/service-tokens#permissions-for-service-account-tokens). +- You must have [develop permissions](/docs/cloud/manage-access/seats-and-users). +- Have [exposures](/docs/build/exposures) configured in your project and [source freshness](/docs/deploy/source-freshness) enabled in the job that generates this exposure. + +## View exposure in dbt Explorer + +First, be sure to enable [source freshness](/docs/deploy/source-freshness) in the job that generates this exposure. + +1. Navigate to dbt Explorer by clicking on the **Explore** link in the navigation. +2. In the main **Overview** page, go to the left navigation. +3. Under the **Resources** tab, click on **Exposures** to view the exposures list. +4. Select a dashboard exposure and go to the **General** tab to view the data health information. +5. In this tab, you’ll see: + - Data health status: Data freshness passed, Data quality passed, Data may be stale, Data quality degraded + - Name of the exposure. + - Resource type (model, source, and so on). + - Dashboard status: Failure, Pass, Stale. + - You can also see the last check completed, the last check time, and the last check duration. +6. You can also click the **Open Dashboard** button on the upper right to immediately view this in your analytics tool. + + + +## Embed in your dashboard + +Once you’ve navigated to the auto-exposure in dbt Explorer, you’ll need to set up your dashboard status tile and [service token](/docs/dbt-cloud-apis/service-tokens): + +1. Go to **Account settings** in dbt Cloud. +2. Select **API tokens** in the left sidebar and then **Service tokens**. +3. Click on **Create service token** and give it a name. +4. Select the [**Metadata Only** permission](/docs/dbt-cloud-apis/service-tokens). This token will be used to embed the exposure tile in your dashboard in the later steps. + + +5. Copy the **Metadata Only token** and save it in a secure location. You'll need it token in the next steps. +6. Navigate back to dbt Explorer and select an exposure. +7. Below the **Data health** section, expand on the toggle for instructions on how to embed the exposure tile (if you're an account admin with develop permissions). +8. In the expanded toggle, you'll see a text field where you can paste your **Metadata Only token**. + + +9. Once you’ve pasted your token, you can select either **URL** or **iFrame** depending on which you need to install into your dashboard. + +If your analytics tool supports iFrames, you can embed the dashboard tile within it. + +### Embed data health tile in Tableau +To embed the data health tile in Tableau, follow these steps: + +1. Ensure you've copied the embed iFrame content in dbt Explorer. +2. For the revamped environment-based exposure tile you can insert these fields into the following iFrame, and then embed them with your dashboard. This is the iFrame that is available from the **Exposure details** page in dbt Explorer. + + ` +``` + +:::tip Replace `YOUR_ACCESS_URL` with your region and plan's Access URL + +dbt Cloud is hosted in multiple regions in the world and each region has a different access URL. Replace `YOUR_ACCESS_URL` with the appropriate [Access URL](/docs/cloud/about-cloud/access-regions-ip-addresses) for your region and plan. For example, if your account is hosted in the EMEA region, you would use the following iFrame code: + +``` + +``` + +::: + +#### Embedding with BI tools +The dashboard status tile should work anywhere you can embed an iFrame. But below are some tactical tips on how to integrate with common BI tools. + + + + +#### Mode +Mode allows you to directly [edit the HTML](https://mode.com/help/articles/report-layout-and-presentation/#html-editor) of any given report, where you can embed the iFrame. + +Note that Mode has also built its own [integration](https://mode.com/get-dbt/) with the dbt Cloud Discovery API! + + + + +#### Looker +Looker does not allow you to directly embed HTML and instead requires creating a [custom visualization](https://docs.looker.com/admin-options/platform/visualizations). One way to do this for admins is to: +- Add a [new visualization](https://fishtown.looker.com/admin/visualizations) on the visualization page for Looker admins. You can use [this URL](https://metadata.cloud.getdbt.com/static/looker-viz.js) to configure a Looker visualization powered by the iFrame. It will look like this: + + + +- Once you have set up your custom visualization, you can use it on any dashboard! You can configure it with the exposure name, job ID, and token relevant to that dashboard. + + + + + + +#### Tableau +Tableau does not require you to embed an iFrame. You only need to use a Web Page object on your Tableau Dashboard and a URL in the following format: + +``` +https://metadata.YOUR_ACCESS_URL/exposure-tile?name=&jobId=&token= +``` + +:::tip Replace `YOUR_ACCESS_URL` with your region and plan's Access URL + +dbt Cloud is hosted in multiple regions in the world and each region has a different access URL. Replace `YOUR_ACCESS_URL` with the appropriate [Access URL](/docs/cloud/about-cloud/access-regions-ip-addresses) for your region and plan. For example, if your account is hosted in the North American region, you would use the following code: + +``` +https://metadata.cloud.getdbt.com/exposure-tile?name=&jobId=&token= + +``` +::: + + + + + + +#### Sigma + +Sigma does not require you to embed an iFrame. Add a new embedded UI element in your Sigma Workbook in the following format: + +``` +https://metadata.YOUR_ACCESS_URL/exposure-tile?name=&jobId=&token= +``` + +:::tip Replace `YOUR_ACCESS_URL` with your region and plan's Access URL + +dbt Cloud is hosted in multiple regions in the world and each region has a different access URL. Replace `YOUR_ACCESS_URL` with the appropriate [Access URL](/docs/cloud/about-cloud/access-regions-ip-addresses) for your region and plan. For example, if your account is hosted in the APAC region, you would use the following code: + +``` +https://metadata.au.dbt.com/exposure-tile?name=&jobId=&token= + +``` +::: + + + + + + diff --git a/website/docs/docs/collaborate/dbt-explorer-faqs.md b/website/docs/docs/collaborate/dbt-explorer-faqs.md index 7533aa8ff99..f9c2a8ae631 100644 --- a/website/docs/docs/collaborate/dbt-explorer-faqs.md +++ b/website/docs/docs/collaborate/dbt-explorer-faqs.md @@ -2,7 +2,7 @@ title: "dbt Explorer FAQs" sidebar_label: "dbt Explorer FAQs" description: "Learn more with the FAQs about dbt Explorer, how it works, how to interact with it, and more." -pagination_next: null +pagination_next: "docs/collaborate/auto-exposures" --- [dbt Explorer](/docs/collaborate/explore-projects) is dbt Cloud’s new knowledge base and lineage visualization experience. It offers an interactive and high-level view of your company’s entire data estate, where you can dive deep into the context you need to understand and improve lineage so your teams can trust the data they’re using to make decisions. diff --git a/website/docs/docs/collaborate/explore-projects.md b/website/docs/docs/collaborate/explore-projects.md index 2c4646fa4d4..e60d019bf2e 100644 --- a/website/docs/docs/collaborate/explore-projects.md +++ b/website/docs/docs/collaborate/explore-projects.md @@ -2,11 +2,12 @@ title: "Discover data with dbt Explorer" sidebar_label: "Discover data with dbt Explorer" description: "Learn about dbt Explorer and how to interact with it to understand, improve, and leverage your dbt projects." -pagination_next: "docs/collaborate/column-level-lineage" +image: /img/docs/collaborate/dbt-explorer/example-project-lineage-graph.png +pagination_next: "docs/collaborate/access-from-dbt-cloud" pagination_prev: null --- -With dbt Explorer, you can view your project's [resources](/docs/build/projects) (such as models, tests, and metrics) and their lineage to gain a better understanding of its latest production state. Navigate and manage your projects within dbt Cloud to help you and other data developers, analysts, and consumers discover and leverage your dbt resources. +With dbt Explorer, you can view your project's [resources](/docs/build/projects) (such as models, tests, and metrics), their lineage, and [model consumption](/docs/collaborate/auto-exposures) to gain a better understanding of its latest production state. Navigate and manage your projects within dbt Cloud to help you and other data developers, analysts, and consumers discover and leverage your dbt resources. import ExplorerCourse from '/snippets/_explorer-course-link.md'; @@ -28,6 +29,8 @@ Navigate the dbt Explorer overview page to access your project's resources and m - **Lineage graph** — Explore your project's or account's [lineage graph](#project-lineage) to visualize the relationships between resources. - **Latest updates** — View the latest changes or issues related to your project's resources, including the most recent job runs, changed properties, lineage, and issues. - **Marts and public models** — View the [marts](/best-practices/how-we-structure/1-guide-overview#guide-structure-overview) and [public models](/docs/collaborate/govern/model-access#access-modifiers) in your project. +- **Model query history** — Use [model query history](/docs/collaborate/model-query-history) to track the history of queries on your models for deeper insights. +- **Auto-exposures** — [Set up and view auto-exposures](/docs/collaborate/auto-exposures) to automatically expose relevant data models from Tableau to enhance visibility. @@ -110,13 +113,14 @@ Lenses are helpful to analyze a subset of the DAG if you're zoomed in, or to fin A resource in your project is characterized by resource type, materialization type, or model layer, as well as its latest run or latest test status. Lenses are available for the following metadata: - **Relationship**: Organizes resources by resource type, such as models, tests, seeds, and [more](/reference/node-selection/syntax). Resource type uses the `resource_type` selector. -- **Materialization Type**: Identifies the strategy for building the dbt models in your data platform. -- **Latest Status**: The status from the latest execution of the resource in the current environment. For example, diagnosing a failed DAG region. -- **Model Layer**: The modeling layer that the model belongs to according to [best practices guide](https://docs.getdbt.com/best-practices/how-we-structure/1-guide-overview#guide-structure-overview). For example, discovering marts models to analyze. +- **Materialization type**: Identifies the strategy for building the dbt models in your data platform. +- **Latest status**: The status from the latest execution of the resource in the current environment. For example, diagnosing a failed DAG region. +- **Model layer**: The modeling layer that the model belongs to according to [best practices guide](https://docs.getdbt.com/best-practices/how-we-structure/1-guide-overview#guide-structure-overview). For example, discovering marts models to analyze. - **Marts** — A model with the prefix `fct_` or `dim_` or a model that lives in the `/marts/` subdirectory. - **Intermediate** — A model with the prefix `int_`. Or, a model that lives in the `/int/` or `/intermediate/` subdirectory. - **Staging** — A model with the prefix `stg_`. Or, a model that lives in the `/staging/` subdirectory. -- **Test Status**: The status from the latest execution of the tests that ran again this resource. In the case that a model has multiple tests with different results, the lens reflects the 'worst case' status. +- **Test status**: The status from the latest execution of the tests that ran again this resource. In the case that a model has multiple tests with different results, the lens reflects the 'worst case' status. +- **Usage queries**: The number of queries against this resource over a given time period. @@ -214,11 +218,12 @@ In the upper right corner of the resource details page, you can: - **Status bar** (below the page title) — Information on the last time the exposure was updated. - **General** tab includes: + - **Data health** — The status on data freshness and data quality. - **Status** section — The status on data freshness and data quality. - - **Lineage** graph — The exposure’s lineage graph. Click the Expand icon in the graph's upper right corner to view the exposure in full lineage graph mode. + - **Lineage** graph — The exposure’s lineage graph. Click the **Expand** icon in the graph's upper right corner to view the exposure in full lineage graph mode. Integrates natively with Tableau and auto-generates downstream lineage. - **Description** section — A description of the exposure. - **Details** section — Details like exposure type, maturity, owner information, and more. - - **Relationships** section — The nodes the exposure **Depends On**. + - **Relationships** section — The nodes the exposure **Depends On**. @@ -257,9 +262,13 @@ Example of the Tests view: ### Example of model details -Example of the details view for the model `customers`: + - +Example of the details view for the model `customers`:
+ + + +
## Staging environment @@ -269,7 +278,6 @@ You can explore the metadata from your production or staging environment to info - ## Related content - [Enterprise permissions](/docs/cloud/manage-access/enterprise-permissions) - [About model governance](/docs/collaborate/govern/about-model-governance) diff --git a/website/docs/docs/collaborate/model-query-history.md b/website/docs/docs/collaborate/model-query-history.md new file mode 100644 index 00000000000..e210d5862fe --- /dev/null +++ b/website/docs/docs/collaborate/model-query-history.md @@ -0,0 +1,100 @@ +--- +title: "Model query history" +sidebar_label: "Model query history" +description: "Import and auto-generate exposures from dashboards and understand how models are used in downstream tools for a richer lineage." +image: /img/docs/collaborate/dbt-explorer/model-query-queried-models.jpg +--- + +# About model query history + +The model query history tile allows you to: + +- View the query count for a model based on the data warehouse's query logs. +- Provides data teams insight, so they can focus their time and infrastructure spend on the worthwhile used data products. +- Enable analysts to find the most popular models used by other people. + +Model query history is powered by a single query of the query log table in your data warehouse aggregated on a daily basis. It filters down to `select` statements only to gauge model consumption and excludes dbt model build and test executions. + +## Prerequisites + +To access the features, you should meet the following: + +1. You have a dbt Cloud account on the [Enterprise plan](https://www.getdbt.com/pricing/). +2. You have set up a [production](https://docs.getdbt.com/docs/deploy/deploy-environments#set-as-production-environment) deployment environment for each project you want to explore, with at least one successful job run. +3. You have [admin permissions](/docs/cloud/manage-access/enterprise-permissions) in dbt Cloud to edit project settings or production environment settings. +4. Use Snowflake or BigQuery as your data warehouse and can enable query history permissions or work with an admin to do so (Support for additional data platforms coming soon). + +## Credential permissions + +This section explains the permissions and steps you need to enable and view model query history in dbt Explorer. + +The model query history feature uses the credentials in your production environment to gather metadata from your data warehouse’s query logs. This means you may need elevated permissions with the warehouse. Before making any changes to your data platform permissions, confirm the configured permissions in dbt Cloud: + +1. Navigate to **Deploy** and then **Environments**. +2. Select the Environment marked **PROD** and click **Settings**. +3. Look at the information under **Deployment credentials**. + - Note: Querying query history entails warehouse costs / uses credits. + + +4. Copy or cross reference those credential permissions with the warehouse permissions and grant your user the right permissions. + + + + This feature makes use of metadata tables available to Snowflake Enterprise tier accounts or higher, `QUERY_HISTORY` and `ACCESS_HISTORY`. The Snowflake user used in the production environment must have `GOVERNANCE_VIEWER` permissions to view the data. + + This can be granted to this user by your `ACCOUNTADMIN` user in Snowflake. For more details, view the snowflake docs [here](https://docs.snowflake.com/en/sql-reference/account-usage#enabling-other-roles-to-use-schemas-in-the-snowflake-database). + + + + + + This feature uses the metadata from the `INFORMATION_SCHEMA.JOBS` view in BigQuery. To access this, the user configured for your production environment must have the following [IAM roles](https://cloud.google.com/bigquery/docs/access-control) for your BigQuery project: + + - `roles/bigquery.resourceViewer` + - `roles/bigquery.jobs.create` + + + +## Enable query history in dbt Cloud + +:::info +During beta, the dbt Labs team will manually enable query history for your dbt Cloud projects. Later on, you’ll be able to do it yourself. + +::: + + +## View query history in Explorer + +To enhance your discovery, you can view your model query history in various locations within dbt Explorer. For details on how to access model query history in each location, expand the following toggles: + +### View from Performance charts + +1. Navigate to dbt Explorer by clicking on the **Explore** link in the navigation. +2. In the main **Overview** page, under **Project** click **Performance** and scroll down to view the most queried models +3. Use the dropdown menu on the right to select the desired time period, with options available for up to the past 3 months. + + + +4. In the model performance tab, open the **Usage** chart to see queries over time for that model. + + +### View from Project lineage + +1. To view your model in your project lineage, go to the main **Overview page** and click on **Project lineage.** +2. In the lower left of your lineage, click on **Lenses** and select **Usage queries**. + + +3. Your lineage should display a small red box above each model, indicating the usage query number for each model. The query number for each model represents the query history over the last 30 days. + +### View from Model list + +1. To view your model in your project lineage, go to the main **Overview page**. +2. In the left navigation, go to the **Resources** tab and click on **Models** to view the models list. +3. You can view the usage query count for the models and sort by most or least queried. The query number for each model represents the query history over the last 30 days. + + diff --git a/website/docs/docs/dbt-cloud-apis/discovery-api.md b/website/docs/docs/dbt-cloud-apis/discovery-api.md index 0345c647dd9..ca84347ffad 100644 --- a/website/docs/docs/dbt-cloud-apis/discovery-api.md +++ b/website/docs/docs/dbt-cloud-apis/discovery-api.md @@ -7,7 +7,7 @@ Every time dbt Cloud runs a project, it generates and stores information about t By leveraging the metadata in dbt Cloud, you can create systems for data monitoring and alerting, lineage exploration, and automated reporting. This can help you improve data discovery, data quality, and pipeline operations within your organization. -You can access the Discovery API through [ad hoc queries](/docs/dbt-cloud-apis/discovery-querying), custom applications, a wide range of [partner ecosystem integrations](https://www.getdbt.com/product/integrations/) (like BI/analytics, catalog and governance, and quality and observability), and by using dbt Cloud features like [model timing](/docs/deploy/run-visibility#model-timing) and [dashboard status tiles](/docs/deploy/dashboard-status-tiles). +You can access the Discovery API through [ad hoc queries](/docs/dbt-cloud-apis/discovery-querying), custom applications, a wide range of [partner ecosystem integrations](https://www.getdbt.com/product/integrations/) (like BI/analytics, catalog and governance, and quality and observability), and by using dbt Cloud features like [model timing](/docs/deploy/run-visibility#model-timing) and [data health tiles]/(docs/collaborate/data-tile). @@ -66,6 +66,9 @@ Use the API to review dataset changes and uses by examining exposures, lineage, + + + diff --git a/website/docs/docs/dbt-cloud-apis/discovery-use-cases-and-examples.md b/website/docs/docs/dbt-cloud-apis/discovery-use-cases-and-examples.md index b01fe6a3b5e..b99853cd547 100644 --- a/website/docs/docs/dbt-cloud-apis/discovery-use-cases-and-examples.md +++ b/website/docs/docs/dbt-cloud-apis/discovery-use-cases-and-examples.md @@ -1040,7 +1040,7 @@ For development use cases, people typically query the historical or latest defin ### How is this model or metric used in downstream tools? [Exposures](/docs/build/exposures) provide a method to define how a model or metric is actually used in dashboards and other analytics tools and use cases. You can query an exposure’s definition to see how project nodes are used and query its upstream lineage results to understand the state of the data used in it, which powers use cases like a freshness and quality status tile. - +
diff --git a/website/docs/docs/deploy/dashboard-status-tiles.md b/website/docs/docs/deploy/dashboard-status-tiles.md deleted file mode 100644 index f1373e36e75..00000000000 --- a/website/docs/docs/deploy/dashboard-status-tiles.md +++ /dev/null @@ -1,102 +0,0 @@ ---- -title: "Dashboard status tiles" -id: "dashboard-status-tiles" -description: "Embed Status Tiles in your dashboards to provide consumers with contextual information about the quality and freshness of data." ---- - -In dbt Cloud, the [Discovery API](/docs/dbt-cloud-apis/discovery-api) can power Dashboard Status Tiles. A Dashboard Status Tile is placed on a dashboard (specifically: anywhere you can embed an iFrame) to give insight into the quality and freshness of the data feeding into that dashboard. This is done via dbt [exposures](/docs/build/exposures). - -## Functionality -The dashboard status tile looks like this: - - - -The data freshness check fails if any sources feeding into the exposure are stale. The data quality check fails if any dbt tests fail. A failure state could look like this: - - - -Clicking into **see details** from the Dashboard Status Tile takes you to a landing page where you can learn more about the specific sources, models, and tests feeding into this exposure. - -## Setup -First, be sure to enable [source freshness](/docs/deploy/source-freshness) in the job that generates this exposure. - -In order to set up your dashboard status tile, here is what you need: - -1. **Metadata Only token.** You can learn how to set up a Metadata-Only token [here](/docs/dbt-cloud-apis/service-tokens). - -2. **Exposure name.** You can learn more about how to set up exposures [here](/docs/build/exposures). - -3. **jobID.** Remember that you can select your jobId directly from the URL when looking at the relevant job in dbt Cloud. - -You can insert these three fields into the following iFrame, and then embed it **anywhere that you can embed an iFrame**: - -``` - -``` - -:::tip Replace `YOUR_ACCESS_URL` with your region and plan's Access URL - -dbt Cloud is hosted in multiple regions in the world and each region has a different access URL. Replace `YOUR_ACCESS_URL` with the appropriate [Access URL](/docs/cloud/about-cloud/access-regions-ip-addresses) for your region and plan. For example, if your account is hosted in the EMEA region, you would use the following iFrame code: - -``` - -``` - -::: - -## Embedding with BI tools -The dashboard status tile should work anywhere you can embed an iFrame. But below are some tactical tips on how to integrate with common BI tools. - -### Mode -Mode allows you to directly [edit the HTML](https://mode.com/help/articles/report-layout-and-presentation/#html-editor) of any given report, where you can embed the iFrame. - -Note that Mode has also built its own [integration](https://mode.com/get-dbt/) with the dbt Cloud Discovery API! - -### Looker -Looker does not allow you to directly embed HTML and instead requires creating a [custom visualization](https://docs.looker.com/admin-options/platform/visualizations). One way to do this for admins is to: -- Add a [new visualization](https://fishtown.looker.com/admin/visualizations) on the visualization page for Looker admins. You can use [this URL](https://metadata.cloud.getdbt.com/static/looker-viz.js) to configure a Looker visualization powered by the iFrame. It will look like this: - - - -- Once you have set up your custom visualization, you can use it on any dashboard! You can configure it with the exposure name, jobID, and token relevant to that dashboard. - - - -### Tableau -Tableau does not require you to embed an iFrame. You only need to use a Web Page object on your Tableau Dashboard and a URL in the following format: - -``` -https://metadata.YOUR_ACCESS_URL/exposure-tile?name=&jobId=&token= -``` - -:::tip Replace `YOUR_ACCESS_URL` with your region and plan's Access URL - -dbt Cloud is hosted in multiple regions in the world and each region has a different access URL. Replace `YOUR_ACCESS_URL` with the appropriate [Access URL](/docs/cloud/about-cloud/access-regions-ip-addresses) for your region and plan. For example, if your account is hosted in the North American region, you would use the following code: - -``` -https://metadata.cloud.getdbt.com/exposure-tile?name=&jobId=&token= - -``` -::: - - - -### Sigma - -Sigma does not require you to embed an iFrame. Add a new embedded UI element in your Sigma Workbook in the following format: - -``` -https://metadata.YOUR_ACCESS_URL/exposure-tile?name=&jobId=&token= -``` - -:::tip Replace `YOUR_ACCESS_URL` with your region and plan's Access URL - -dbt Cloud is hosted in multiple regions in the world and each region has a different access URL. Replace `YOUR_ACCESS_URL` with the appropriate [Access URL](/docs/cloud/about-cloud/access-regions-ip-addresses) for your region and plan. For example, if your account is hosted in the APAC region, you would use the following code: - -``` -https://metadata.au.dbt.com/exposure-tile?name=&jobId=&token= - -``` -::: - - diff --git a/website/docs/docs/deploy/deployment-overview.md b/website/docs/docs/deploy/deployment-overview.md index 539b083e42e..11575e6b0b7 100644 --- a/website/docs/docs/deploy/deployment-overview.md +++ b/website/docs/docs/deploy/deployment-overview.md @@ -15,7 +15,7 @@ dbt Cloud offers the easiest and most reliable way to run your dbt project in pr - Ensure CI and production pipelines are efficient - Identify the root cause of failures in deployment environments - Maintain high-quality code and data in production -- Gain visibility into the health of deployment jobs, models, and tests +- Gain visibility into the [health](/docs/collaborate/data-tile) of deployment jobs, models, and tests - Uses [exports](/docs/use-dbt-semantic-layer/exports) to write [saved queries](/docs/build/saved-queries) in your data platform for reliable and fast metric reporting Before continuing, make sure you understand dbt's approach to [deployment environments](/docs/deploy/deploy-environments). @@ -97,12 +97,6 @@ Learn how to use dbt Cloud's features to help your team ship timely and quality link="/docs/deploy/source-freshness" icon="dbt-bit"/> - -
diff --git a/website/docs/docs/deploy/monitor-jobs.md b/website/docs/docs/deploy/monitor-jobs.md index 0a9f88ff94a..8382743dd03 100644 --- a/website/docs/docs/deploy/monitor-jobs.md +++ b/website/docs/docs/deploy/monitor-jobs.md @@ -16,7 +16,8 @@ This portion of our documentation will go over dbt Cloud's various capabilities - [Webhooks](/docs/deploy/webhooks) — Use webhooks to send events about your dbt jobs' statuses to other systems. - [Leverage artifacts](/docs/deploy/artifacts) — dbt Cloud generates and saves artifacts for your project, which it uses to power features like creating docs for your project and reporting freshness of your sources. - [Source freshness](/docs/deploy/source-freshness) — Monitor data governance by enabling snapshots to capture the freshness of your data sources. -- [Dashboard status tiles](/docs/deploy/dashboard-status-tiles) — Set up and add status tiles to view data freshness and quality checks + +To set up and add data health tiles to view data freshness and quality checks in your dashboard, refer to [data health tiles](/docs/collaborate/data-tile). diff --git a/website/docs/guides/productionize-your-dbt-databricks-project.md b/website/docs/guides/productionize-your-dbt-databricks-project.md index bada787e01f..1e757e9cf0a 100644 --- a/website/docs/guides/productionize-your-dbt-databricks-project.md +++ b/website/docs/guides/productionize-your-dbt-databricks-project.md @@ -109,7 +109,7 @@ The deployment monitor in dbt Cloud offers a higher-level view of your run histo -By adding [status tiles](/docs/deploy/dashboard-status-tiles) to your BI dashboards, you can give stakeholders visibility into the health of your data pipeline without leaving their preferred interface. Status tiles instill confidence in your data and help prevent unnecessary inquiries or context switching. To implement dashboard status tiles, you'll need to have dbt docs with [exposures](/docs/build/exposures) defined. +By adding [data health tiles](/docs/collaborate/data-tile) to your BI dashboards, you can give stakeholders visibility into the health of your data pipeline without leaving their preferred interface. Data tiles instill confidence in your data and help prevent unnecessary inquiries or context switching. To implement dashboard status tiles, you'll need to have dbt docs with [exposures](/docs/build/exposures) defined. ## Set up notifications diff --git a/website/sidebars.js b/website/sidebars.js index 589dbd4a27d..a3b0cd2d8a4 100644 --- a/website/sidebars.js +++ b/website/sidebars.js @@ -488,7 +488,6 @@ const sidebarSettings = { "docs/deploy/webhooks", "docs/deploy/artifacts", "docs/deploy/source-freshness", - "docs/deploy/dashboard-status-tiles", ], }, "docs/deploy/deployment-tools", @@ -506,12 +505,25 @@ const sidebarSettings = { link: { type: "doc", id: "docs/collaborate/explore-projects" }, items: [ "docs/collaborate/explore-projects", + "docs/collaborate/access-from-dbt-cloud", "docs/collaborate/column-level-lineage", "docs/collaborate/model-performance", "docs/collaborate/project-recommendations", "docs/collaborate/explore-multiple-projects", - "docs/collaborate/access-from-dbt-cloud", "docs/collaborate/dbt-explorer-faqs", + { + type: "category", + label: "Model consumption", + link: { + type: "doc", + id: "docs/collaborate/auto-exposures", + }, + items: [ + "docs/collaborate/auto-exposures", + "docs/collaborate/data-tile", + "docs/collaborate/model-query-history", + ], + }, ], }, { @@ -695,6 +707,7 @@ const sidebarSettings = { link: { type: "doc", id: "docs/cloud-integrations/overview" }, items: [ "docs/cloud-integrations/overview", + "docs/cloud-integrations/configure-auto-exposures", { type: "category", label: "Snowflake Native App", diff --git a/website/snippets/_auto-exposures-view.md b/website/snippets/_auto-exposures-view.md new file mode 100644 index 00000000000..95f81782cab --- /dev/null +++ b/website/snippets/_auto-exposures-view.md @@ -0,0 +1,20 @@ +## View auto-exposures in dbt Explorer + +After setting up auto-exposures in dbt Cloud, you can view them in dbt Explorer for a richer experience: +1. Navigate to dbt Explorer by clicking on the **Explore** link in the navigation. +2. From the **Overview** page, you can view auto-exposures from a couple of places: + - From the **Exposures** menu item under **Resources**. This menu provides a comprehensive list of all the exposures so you can quickly access and manage them. + + + - Locate directly from within the **File tree** under the **imported_from_tableau** sub-folder. This view integrates exposures seamlessly with your project files, making it easy to find and reference them from your project's structure. + + + - From the **Project lineage** view, which visualizes the dependencies and relationships in your project. 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