diff --git a/docs-website/sidebars.js b/docs-website/sidebars.js
index 57faeec74c..a565dafcdd 100644
--- a/docs-website/sidebars.js
+++ b/docs-website/sidebars.js
@@ -105,6 +105,17 @@ module.exports = {
// "docs/wip/guide-enrich-your-metadata",
],
},
+ {
+ "Ingestion Quickstart Guides": [
+ {
+ BigQuery: [
+ "docs/quick-ingestion-guides/bigquery/overview",
+ "docs/quick-ingestion-guides/bigquery/setup",
+ "docs/quick-ingestion-guides/bigquery/configuration",
+ ],
+ },
+ ],
+ },
],
"Ingest Metadata": [
// The purpose of this section is to provide a deeper understanding of how ingestion works.
diff --git a/docs/quick-ingestion-guides/bigquery/configuration.md b/docs/quick-ingestion-guides/bigquery/configuration.md
new file mode 100644
index 0000000000..ed43f10ddf
--- /dev/null
+++ b/docs/quick-ingestion-guides/bigquery/configuration.md
@@ -0,0 +1,150 @@
+---
+title: Configuration
+---
+# Configuring Your BigQuery Connector to DataHub
+
+Now that you have created a Service Account and Service Account Key in BigQuery in [the prior step](setup.md), it's now time to set up a connection via the DataHub UI.
+
+## Configure Secrets
+
+1. Within DataHub, navigate to the **Ingestion** tab in the top, right corner of your screen
+
+
+ 
+
+
+:::note
+If you do not see the Ingestion tab, please contact your DataHub admin to grant you the correct permissions
+:::
+
+2. Navigate to the **Secrets** tab and click **Create new secret**
+
+
+ 
+
+
+
+3. Create a Private Key secret
+
+This will securely store your BigQuery Service Account Private Key within DataHub
+
+ * Enter a name like `BIGQUERY_PRIVATE_KEY` - we will use this later to refer to the secret
+ * Copy and paste the `private_key` value from your Service Account Key
+ * Optionally add a description
+ * Click **Create**
+
+
+ 
+
+
+4. Create a Private Key ID secret
+
+This will securely store your BigQuery Service Account Private Key ID within DataHub
+
+ * Click **Create new secret** again
+ * Enter a name like `BIGQUERY_PRIVATE_KEY_ID` - we will use this later to refer to the secret
+ * Copy and paste the `private_key_id` value from your Service Account Key
+ * Optionally add a description
+ * Click **Create**
+
+
+ 
+
+
+## Configure Recipe
+
+5. Navigate to the **Sources** tab and click **Create new source**
+
+
+ 
+
+
+6. Select BigQuery
+
+
+ 
+
+
+7. Fill out the BigQuery Recipe
+
+You can find the following details in your Service Account Key file:
+
+* Project ID
+* Client Email
+* Client ID
+
+Populate the Secret Fields by selecting the Primary Key and Primary Key ID secrets you created in steps 3 and 4.
+
+
+ 
+
+
+8. Click **Test Connection**
+
+This step will ensure you have configured your credentials accurately and confirm you have the required permissions to extract all relevant metadata.
+
+
+ 
+
+
+After you have successfully tested your connection, click **Next**.
+
+## Schedule Execution
+
+Now it's time to schedule a recurring ingestion pipeline to regularly extract metadata from your BigQuery instance.
+
+9. Decide how regularly you want this ingestion to run-- day, month, year, hour, minute, etc. Select from the dropdown
+
+ 
+
+
+10. Ensure you've configured your correct timezone
+
+ 
+
+
+11. Click **Next** when you are done
+
+## Finish Up
+
+12. Name your ingestion source, then click **Save and Run**
+
+ 
+
+
+You will now find your new ingestion source running
+
+
+ 
+
+
+## Validate Ingestion Runs
+
+13. View the latest status of ingestion runs on the Ingestion page
+
+
+ 
+
+
+14. Click the plus sign to expand the full list of historical runs and outcomes; click **Details** to see the outcomes of a specific run
+
+
+ 
+
+
+15. From the Ingestion Run Details page, pick **View All** to see which entities were ingested
+
+
+ 
+
+
+16. Pick an entity from the list to manually validate if it contains the detail you expected
+
+
+ 
+
+
+
+**Congratulations!** You've successfully set up BigQuery as an ingestion source for DataHub!
+
+*Need more help? Join the conversation in [Slack](http://slack.datahubproject.io)!*
diff --git a/docs/quick-ingestion-guides/bigquery/overview.md b/docs/quick-ingestion-guides/bigquery/overview.md
new file mode 100644
index 0000000000..8cd6879847
--- /dev/null
+++ b/docs/quick-ingestion-guides/bigquery/overview.md
@@ -0,0 +1,37 @@
+---
+title: Overview
+---
+# BigQuery Ingestion Guide: Overview
+
+## What You Will Get Out of This Guide
+
+This guide will help you set up the BigQuery connector through the DataHub UI to begin ingesting metadata into DataHub.
+
+Upon completing this guide, you will have a recurring ingestion pipeline that will extract metadata from BigQuery and load it into DataHub. This will include to following BigQuery asset types:
+
+* [Projects](https://cloud.google.com/bigquery/docs/resource-hierarchy#projects)
+* [Datasets](https://cloud.google.com/bigquery/docs/datasets-intro)
+* [Tables](https://cloud.google.com/bigquery/docs/tables-intro)
+* [Views](https://cloud.google.com/bigquery/docs/views-intro)
+* [Materialized Views](https://cloud.google.com/bigquery/docs/materialized-views-intro)
+
+This recurring ingestion pipeline will also extract:
+
+* **Usage statistics** to help you understand recent query activity
+* **Table-level lineage** (where available) to automatically define interdependencies between datasets
+* **Table- and column-level profile statistics** to help you understand the shape of the data
+
+:::caution
+You will NOT have extracted [Routines](https://cloud.google.com/bigquery/docs/routines), [Search Indexes](https://cloud.google.com/bigquery/docs/search-intro) from BigQuery, as the connector does not support ingesting these assets
+:::
+
+## Next Steps
+If that all sounds like what you're looking for, navigate to the [next page](setup.md), where we'll talk about prerequisites
+
+## Advanced Guides and Reference
+If you're looking to do something more in-depth, want to use CLI instead of the DataHub UI, or just need to look at the reference documentation for this connector, use these links:
+
+* Learn about CLI Ingestion in the [Introduction to Metadata Ingestion](../../../metadata-ingestion/README.md)
+* [BigQuery Ingestion Reference Guide](https://datahubproject.io/docs/generated/ingestion/sources/bigquery/#module-bigquery)
+
+*Need more help? Join the conversation in [Slack](http://slack.datahubproject.io)!*
diff --git a/docs/quick-ingestion-guides/bigquery/setup.md b/docs/quick-ingestion-guides/bigquery/setup.md
new file mode 100644
index 0000000000..3635ea66f7
--- /dev/null
+++ b/docs/quick-ingestion-guides/bigquery/setup.md
@@ -0,0 +1,60 @@
+---
+title: Setup
+---
+# BigQuery Ingestion Guide: Setup & Prerequisites
+
+To configure ingestion from BigQuery, you'll need a [Service Account](https://cloud.google.com/iam/docs/creating-managing-service-accounts) configured with the proper permission sets, and an associated [Service Account Key](https://cloud.google.com/iam/docs/creating-managing-service-account-keys).
+
+This setup guide will walk you through the steps you'll need to take via your Google Cloud Console.
+
+## BigQuery Prerequisites
+
+If you do not have an existing Service Account and Service Account Key, please work with your BigQuery Admin to ensure you have the appropriate permissions and/or roles to continue with this setup guide.
+
+When creating and managing new Service Accounts and Service Account Keys, we have found the following permissions and roles to be required:
+
+* Create a Service Account: `iam.serviceAccounts.create` permission
+* Assign roles to a Service Account: `serviceusage.services.enable` permission
+* Set permission policy to the project: `resourcemanager.projects.setIamPolicy` permission
+* Generate Key for Service Account: Service Account Key Admin (`roles/iam.serviceAccountKeyAdmin`) IAM role
+
+:::note
+Please refer to the BigQuery [Permissions](https://cloud.google.com/iam/docs/permissions-reference) and [IAM Roles](https://cloud.google.com/iam/docs/understanding-roles) references for details
+:::
+
+## BigQuery Setup
+
+1. To set up a new Service Account follow [this guide](https://cloud.google.com/iam/docs/creating-managing-service-accounts)
+
+2. When you are creating a Service Account, assign the following predefined Roles:
+ - [BigQuery Job User](https://cloud.google.com/bigquery/docs/access-control#bigquery.jobUser)
+ - [BigQuery Metadata Viewer](https://cloud.google.com/bigquery/docs/access-control#bigquery.metadataViewer)
+ - [BigQuery Resource Viewer](https://cloud.google.com/bigquery/docs/access-control#bigquery.resourceViewer) -> This role is for Table-Level Lineage and Usage extraction
+ - [Logs View Accessor](https://cloud.google.com/bigquery/docs/access-control#bigquery.dataViewer) -> This role is for Table-Level Lineage and Usage extraction
+ - [BigQuery Data Viewer](https://cloud.google.com/bigquery/docs/access-control#bigquery.dataViewer) -> This role is for Profiling
+
+:::note
+You can always add/remove roles to Service Accounts later on. Please refer to the BigQuery [Manage access to projects, folders, and organizations](https://cloud.google.com/iam/docs/granting-changing-revoking-access) guide for more details.
+:::
+
+3. Create and download a [Service Account Key](https://cloud.google.com/iam/docs/creating-managing-service-account-keys). We will use this to set up authentication within DataHub.
+
+The key file looks like this:
+```json
+{
+ "type": "service_account",
+ "project_id": "project-id-1234567",
+ "private_key_id": "d0121d0000882411234e11166c6aaa23ed5d74e0",
+ "private_key": "-----BEGIN PRIVATE KEY-----\nMIIyourkey\n-----END PRIVATE KEY-----",
+ "client_email": "test@suppproject-id-1234567.iam.gserviceaccount.com",
+ "client_id": "113545814931671546333",
+ "auth_uri": "https://accounts.google.com/o/oauth2/auth",
+ "token_uri": "https://oauth2.googleapis.com/token",
+ "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
+ "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/test%suppproject-id-1234567.iam.gserviceaccount.com"
+}
+```
+## Next Steps
+Once you've confirmed all of the above in BigQuery, it's time to [move on](configuration.md) to configure the actual ingestion source within the DataHub UI.
+
+*Need more help? Join the conversation in [Slack](http://slack.datahubproject.io)!*