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[WIP] Fix stale/incorrect content across existing DO docs #37964

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2 changes: 1 addition & 1 deletion content/en/data_observability/data_catalog.md
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Expand Up @@ -32,7 +32,7 @@ When you open the catalog at [/data-obs/catalog](https://app.datadoghq.com/data-
- **Description**: pulled from the source system if available
- **Links to the source system**: direct references back to the origin platform so you can navigate from the catalog to the source in one click
- **Tags**: `key:value` metadata pairs pulled from the source system if available
- **Monitor Status**: displays the state of any active [Data Quality Monitors](/data_observability/quality_monitoring/) on the asset
- **Monitor Status**: displays the state of any active [Data Observability monitors](/data_observability/quality_monitoring/) on the asset
- **Lineage**: upstream and downstream dependencies, where supported by the integration. To explore lineage across assets, see [Lineage][1].

Use the left sidebar to filter assets by type: {{< ui >}}All assets{{< /ui >}}, {{< ui >}}Databases{{< /ui >}}, {{< ui >}}Schemas{{< /ui >}}, or {{< ui >}}Tables{{< /ui >}}. Connected integrations (such as Snowflake, dbt, and BigQuery) are also listed individually in the sidebar.
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10 changes: 5 additions & 5 deletions content/en/data_observability/jobs_monitoring/_index.md
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Expand Up @@ -34,8 +34,8 @@ Data Observability: Jobs Monitoring provides visibility into the performance, re
Data Observability: Jobs Monitoring supports multiple job technologies. To get started, select your technology and follow the installation instructions:

{{< card-grid >}}
{{< image-card href="/data_jobs/databricks/" src="integrations_logos/databricks.png" alt="Databricks" >}}
{{< image-card href="/data_jobs/airflow/" src="integrations_logos/airflow.png" alt="Airflow" >}}
{{< image-card href="/data_observability/jobs_monitoring/databricks/" src="integrations_logos/databricks.png" alt="Databricks" >}}
{{< image-card href="/data_observability/jobs_monitoring/airflow/" src="integrations_logos/airflow.png" alt="Airflow" >}}
{{< image-card href="/data_observability/jobs_monitoring/dbt" src="integrations_logos/dbt-cloud_large.svg" alt="dbt cloud" >}}
{{< image-card href="/data_observability/jobs_monitoring/glue/" src="integrations_logos/amazon_glue.png" alt="AWS Glue" >}}
{{< /card-grid >}}
Expand All @@ -45,9 +45,9 @@ Data Observability: Jobs Monitoring supports multiple job technologies. To get s
Data Observability: Jobs Monitoring also supports Apache Spark jobs on the following platforms:

{{< card-grid >}}
{{< image-card href="/data_jobs/kubernetes/" src="integrations_logos/kubernetes.png" alt="Kubernetes" >}}
{{< image-card href="/data_jobs/emr" src="integrations_logos/amazon_emr.png" alt="Amazon EMR" >}}
{{< image-card href="/data_jobs/dataproc/" src="integrations_logos/google_cloud_dataproc.png" alt="GCP Dataproc" >}}
{{< image-card href="/data_observability/jobs_monitoring/kubernetes/" src="integrations_logos/kubernetes.png" alt="Kubernetes" >}}
{{< image-card href="/data_observability/jobs_monitoring/emr" src="integrations_logos/amazon_emr.png" alt="Amazon EMR" >}}
{{< image-card href="/data_observability/jobs_monitoring/dataproc/" src="integrations_logos/google_cloud_dataproc.png" alt="GCP Dataproc" >}}
{{< /card-grid >}}

<br/>
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2 changes: 1 addition & 1 deletion content/en/data_observability/jobs_monitoring/airflow.md
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Expand Up @@ -205,7 +205,7 @@ To get started, follow the instructions below.

1. Deploy your updated `requirements.txt` and [Amazon MWAA startup script][3] to your Amazon S3 folder configured for your Amazon MWAA Environment.

1. Optionally, set up Log Collection for correlating task logs to DAG run executions in DJM:
1. Optionally, set up Log Collection for correlating task logs to DAG run executions in Jobs Monitoring:
1. Configure Amazon MWAA to [send logs to CloudWatch][9].
2. [Send the logs to Datadog][10].

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2 changes: 1 addition & 1 deletion content/en/data_observability/jobs_monitoring/databricks/_index.md
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Expand Up @@ -417,7 +417,7 @@ If some jobs are not visible, navigate to the [Configuration][9] page to underst

## Troubleshooting

If you don't see any data in DJM after installing the product, follow these steps.
If you don't see any data in Jobs Monitoring after installing the product, follow these steps.

### Init script not running or failing

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1 change: 0 additions & 1 deletion content/en/data_observability/jobs_monitoring/dataproc.md
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Expand Up @@ -115,7 +115,6 @@ In Datadog, view the [Data Observability: Jobs Monitoring][8] page to see a list
[3]: https://cloud.google.com/secret-manager/docs/secret-rotation?_gl=1*144zyx0*_ga*MTk0ODY1OTU1OS4xNzI0NzA5NDM4*_ga_WH2QY8WWF5*MTcyNTk1MDU4Mi4yMy4xLjE3MjU5Nzk3NzUuNDEuMC4w
[4]: https://console.cloud.google.com/dataproc/
[5]: https://console.cloud.google.com/iam-admin/iam
[7]: /getting_started/site/
[8]: https://app.datadoghq.com/data-jobs/
[9]: /data_jobs
[10]: https://cloud.google.com/dataproc/docs/concepts/versioning/overview
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3 changes: 1 addition & 2 deletions content/en/data_observability/jobs_monitoring/emr.md
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Expand Up @@ -11,7 +11,7 @@ further_reading:

[Data Observability: Jobs Monitoring][9] gives visibility into the performance and reliability of Apache Spark applications on Amazon EMR.

If you are using [EMR on EKS][13], follow these [instructions for setting up DJM on Kubernetes][14].
If you are using [EMR on EKS][13], follow these [instructions for setting up Jobs Monitoring on Kubernetes][14].

## Requirements

Expand Down Expand Up @@ -179,7 +179,6 @@ In Datadog, view the [Data Observability: Jobs Monitoring][8] page to see a list
[3]: https://docs.aws.amazon.com/secretsmanager/latest/userguide/rotating-secrets.html
[4]: https://console.aws.amazon.com/emr
[5]: https://console.aws.amazon.com/iam/
[7]: /getting_started/site/
[8]: https://app.datadoghq.com/data-jobs/
[9]: /data_jobs
[10]: https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-601-release.html
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2 changes: 1 addition & 1 deletion content/en/data_observability/jobs_monitoring/glue.md
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Expand Up @@ -148,7 +148,7 @@ In Datadog, view the [Data Observability: Jobs Monitoring][6] page to see a list
{{< partial name="whats-next/whats-next.html" >}}

[1]: /integrations/amazon-web-services/
[2]: https://app.datadoghq.com/datasets/settings/integrations
[2]: https://app.datadoghq.com/data-obs/settings/integrations
[4]: /integrations/amazon-glue/
[5]: /logs/guide/send-aws-services-logs-with-the-datadog-lambda-function/?tab=awsconsole
[6]: https://app.datadoghq.com/data-jobs/
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1 change: 0 additions & 1 deletion content/en/data_observability/quality_monitoring/business_intelligence/looker.md
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Expand Up @@ -55,7 +55,6 @@ After syncing, you can explore your Looker assets and their upstream dependencie

{{< partial name="whats-next/whats-next.html" >}}

[1]: https://cloud.google.com/looker/docs/api-auth
[2]: https://app.datadoghq.com/integrations/looker
[3]: https://app.datadoghq.com/data-obs/catalog
[4]: https://app.datadoghq.com/integrations/github
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4 changes: 2 additions & 2 deletions content/en/data_observability/quality_monitoring/data_lakes/aws_glue.md
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Expand Up @@ -218,8 +218,8 @@ After the sync completes, your tables appear in the [Data Catalog][3]. You can a
{{< partial name="whats-next/whats-next.html" >}}

[1]: /integrations/amazon-web-services/
[2]: https://app.datadoghq.com/datasets/settings/integrations
[3]: https://app.datadoghq.com/datasets/catalog?integration=awsglue%2Fdatabase_account
[2]: https://app.datadoghq.com/data-obs/settings/integrations
[3]: https://app.datadoghq.com/data-obs/catalog?integration=awsglue%2Fdatabase_account
[4]: https://docs.aws.amazon.com/glue/latest/dg/security_iam_id-based-policy-examples.html
[5]: https://docs.aws.amazon.com/glue/latest/dg/aws-glue-programming-etl-format-iceberg.html
[6]: /integrations/amazon-glue/
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2 changes: 1 addition & 1 deletion content/en/data_observability/quality_monitoring/data_warehouses/bigquery.md
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Expand Up @@ -120,7 +120,7 @@ After the initial sync completes, create a [Data Observability monitor][14] to s
[5]: https://cloud.google.com/iam/docs/roles-permissions/monitoring#monitoring.viewer
[6]: https://cloud.google.com/iam/docs/roles-permissions/cloudasset#cloudasset.viewer
[7]: https://cloud.google.com/iam/docs/roles-permissions/browser#browser
[8]: https://app.datadoghq.com/datasets/settings/integrations
[8]: https://app.datadoghq.com/data-obs/settings/integrations
[9]: https://cloud.google.com/monitoring/api/enable-api
[10]: https://cloud.google.com/asset-inventory/docs/reference/rest
[11]: https://cloud.google.com/compute/docs/reference/rest/v1
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12 changes: 6 additions & 6 deletions content/en/data_observability/quality_monitoring/data_warehouses/databricks.md
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Expand Up @@ -53,8 +53,8 @@ Use the full catalog access option for simpler setup. It automatically includes


```sql
GRANT USE_CATALOG ON CATALOG <catalog_name> TO `<application_id>`;
GRANT USE_SCHEMA ON CATALOG <catalog_name> TO `<application_id>`;
GRANT USE CATALOG ON CATALOG <catalog_name> TO `<application_id>`;
GRANT USE SCHEMA ON CATALOG <catalog_name> TO `<application_id>`;
GRANT SELECT ON CATALOG <catalog_name> TO `<application_id>`;
```

Expand All @@ -64,8 +64,8 @@ GRANT SELECT ON CATALOG <catalog_name> TO `<application_id>`;
Use the specific tables option for least-privilege access or if you only need to monitor a subset of your data. You must update permissions when adding new tables.

```sql
GRANT USE_CATALOG ON CATALOG <catalog_name> TO `<application_id>`;
GRANT USE_SCHEMA ON SCHEMA <catalog_name>.<schema_name> TO `<application_id>`;
GRANT USE CATALOG ON CATALOG <catalog_name> TO `<application_id>`;
GRANT USE SCHEMA ON SCHEMA <catalog_name>.<schema_name> TO `<application_id>`;
GRANT SELECT ON TABLE <catalog_name>.<schema_name>.<table_name> TO `<application_id>`;
```

Expand All @@ -74,8 +74,8 @@ GRANT SELECT ON TABLE <catalog_name>.<schema_name>.<table_name> TO `<application

These permissions are needed for the following reasons:

- `GRANT USE_CATALOG` is required to navigate into the catalog and discover schemas.
- `GRANT USE_SCHEMA` is required to enumerate tables and monitor schema-level health.
- `GRANT USE CATALOG` is required to navigate into the catalog and discover schemas.
- `GRANT USE SCHEMA` is required to enumerate tables and monitor schema-level health.
- `GRANT SELECT` is required for data quality monitoring, such as custom SQL or distribution checks.

## Next steps
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2 changes: 1 addition & 1 deletion content/en/data_observability/quality_monitoring/data_warehouses/redshift.md
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Expand Up @@ -184,6 +184,6 @@ After the initial sync completes, create a [Data Observability monitor][2] to st

{{< partial name="whats-next/whats-next.html" >}}

[1]: https://app.datadoghq.com/datasets/settings/integrations
[1]: https://app.datadoghq.com/data-obs/settings/integrations
[2]: /monitors/types/data_observability/
[3]: /integrations/amazon-web-services/
2 changes: 1 addition & 1 deletion content/en/data_observability/quality_monitoring/data_warehouses/snowflake.md
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Expand Up @@ -249,7 +249,7 @@ If Datadog is unable to see expected databases, schemas, or tables in your Snowf

[1]: https://docs.snowflake.com/en/user-guide/key-pair-auth#generate-the-private-key
[2]: https://docs.snowflake.com/en/developer-guide/logging-tracing/event-table-setting-up
[3]: https://app.datadoghq.com/datasets/settings/integrations
[3]: https://app.datadoghq.com/data-obs/settings/integrations
[4]: https://app.datadoghq.com/apm/traces
[5]: /monitors/types/data_observability/
[6]: https://docs.snowflake.com/en/user-guide/object-tagging
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