# Query Tags

## Overview

Query Tags are key-value metadata that Seemore automatically extracts from your Snowflake queries. Each time a query runs, Seemore inspects the SQL comments and the Snowflake `QUERY_TAG` property to identify which tool or pipeline issued it and attaches structured tags to the query record.

This lets you slice cost and performance data by the tools and workflows behind your queries — without any manual labeling.

***

## Default Supported Tags

Seemore ships with built-in extraction for the following integrations. Tags appear in the format `Integration.TagName` (e.g., `DBT.NodeName`).

| Integration     | Tags                                                                           |
| --------------- | ------------------------------------------------------------------------------ |
| **Tableau**     | SiteLuid, UserLuid, WorkbookLuid, WorksheetLuid, DashboardLuid, ConnectionType |
| **Looker**      | UserId, InstanceSlug                                                           |
| **Power BI**    | Host, HostContext, PowerQuery                                                  |
| **ThoughtSpot** | type, task, isRLSApplied, storable.type                                        |
| **Airflow**     | DagId                                                                          |
| **Hex**         | ProjectId, ProjectName, Status, UserEmail, Context                             |
| **dbt**         | NodeName, NodeSchema, NodeDatabase, CloudJobId                                 |

In addition, every matched query receives a special **Integration** tag that identifies which tool issued it (e.g., `Tableau`, `Looker`, `DBT`).

***

## Where Query Tags Are Supported

### Data Cloud — Workloads

On the **Data Cloud → Workloads** screen you can use query tags in two ways:

* **Filter** — select a tag key and one or more values in the **Query Tags** filter to narrow the workload view to matching queries.

<figure><img src="https://3620459840-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FnSbIoBjUxWTGNWa9gGw7%2Fuploads%2Fgit-blob-229a66887c96633e95b6c70d9e89d96770a313de%2Fquery-tags-filter.png?alt=media" alt="Filtering workloads by query tag values"><figcaption><p>Filtering workloads by query tag values</p></figcaption></figure>

* **Group by** — open the **Group by** dropdown, switch to **Tags**, and select a tag key to group the cost breakdown by that tag's values.

<figure><img src="https://3620459840-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FnSbIoBjUxWTGNWa9gGw7%2Fuploads%2Fgit-blob-bb5d1811c1ffca71d7f4fe96914e949d07e7c1ec%2Fquery-tags-group-by.png?alt=media" alt="Grouping workloads by query tag"><figcaption><p>Grouping workloads by query tag</p></figcaption></figure>

### Query History

The **Query History** screen includes a **Query Tags** filter that lets you narrow the query list to entries matching specific tag key-value pairs.

### Domains

When creating or editing a **Domain** in **Settings → Domains**, you can include query tag criteria so the domain automatically filters all platform screens to queries matching those tags.

***

## Custom Tags & Support

If your integration is not listed above, or you use custom `QUERY_TAG` values on your Snowflake queries, or you embed custom metadata in SQL comments — reach out to SeeMore Data support. We can configure custom tag extraction tailored to your environment so that your tags appear alongside the built-in ones throughout the platform.

{% hint style="info" %}
Using **dbt Core**? See the [dbt Core integration guide](https://docs.seemoredata.io/external-docs/fundamentals/getting-set-up/setting-integrations/dbt/dbt-core) for instructions on setting up the `dbt-snowflake-query-tags` package so Seemore can extract dbt metadata from your queries.
{% endhint %}


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.seemoredata.io/external-docs/fundamentals/our-features/observability/query-tags.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.