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> of the [Service Specific
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Data relationships in Knowledge Catalog (formerly Dataplex Universal Catalog) let you find related
BigQuery tables and views and inspect how they connect. You can then
explore linked datasets or provide structural context to AI agents for more
accurate query generation.

## Before you begin

Before you view relationships between data assets, ensure that you are granted
the required roles.

### Required roles

To view relationships between data assets in Knowledge Catalog, you don't
need any IAM roles specific to Knowledge Catalog.
Knowledge Catalog uses your existing permissions on the source systems
where the assets reside, such as BigQuery, to determine your
ability to see relationships. For example, to see relationships involving a
BigQuery table, you need the `bigquery.tables.get` permission.

If you don't have the permission to view an asset in its source system, the Knowledge Catalog relationships graph hides any
relationships that involve that asset. This ensures that relationship visibility adheres to the
security boundaries and permissions established in the source systems.

## About data relationships

Data relationships illustrate how data assets connect. For example, if you
locate a table with customer data, its relationships can reveal related tables
listing orders or support tickets. Additionally, relationships act as a
structural guide, providing essential context to Large Language Models. As a
result, AI generates more precise responses, formulating accurate queries to
retrieve specific information.

Knowledge Catalog automatically discovers and stores potential links and
common relationships between data assets, helping you understand the nature of
each connection. The relationship data originates from various sources, such as
the following:

- Historical query logs Knowledge Catalog that continuously analyze query history to detect potential `JOIN` patterns between tables.
- [Data insights](https://docs.cloud.google.com/knowledge-catalog/docs/data-insights-structured-data.md.txt) suggest data relationships on demand by analyzing schema attributes and data overlaps using large language models.

### Supported data assets

You can view data relationships for BigQuery tables and views.

## View data relationships

To view data relationships for BigQuery tables and views, use
Google Cloud console or Dataplex API.

### console

To view data relationships for a table in BigQuery, do the
following:

1. In the Google Cloud console, go to the Knowledge Catalog **Search** page.

   [Go to Search](https://console.cloud.google.com/dataplex)
2. Search for a BigQuery table that you want to view relationships for.

3. In the search results, click the table name to open its entry page.

4. Go to the **Relationships** tab to view the following information about each data
   relationship:

   - **Target**: The name of the connected data asset.
   - **Relationship**: The specific columns used to link the assets.
   - **Type:** The nature of the link. For example, both frequent joins and relationships discovered by data insights appear as `JOIN`.
   - **Origin:** The origin of the relationship.

     - `Query history` is the origin for frequent joins.
     - `Data insights` is the origin for relationships discovered by data insights.
   - **Action:** A sample query that you can use to discover the link between the assets.

### REST

Discovered relationships are stored in Knowledge Catalog as
[`EntryLinks`](https://docs.cloud.google.com/knowledge-catalog/docs/reference/rest/v1/projects.locations.entryGroups.entryLinks.md.txt)
that establish a relationship between two data assets (entries) in
Knowledge Catalog. The details about the relationship, such as the
joined columns and the relationship source, are stored as aspects of
`EntryLinks`.

To view data relationships, use the following methods:

- [`LookupEntryLinks`](https://docs.cloud.google.com/knowledge-catalog/docs/reference/rest/v1/projects.locations/lookupEntryLinks.md.txt)
  retrieves all `EntryLinks` that reference a specific data entry as either
  the source or the target to return the full set of relationships associated
  with a given entry.

- [`LookupContext`](https://docs.cloud.google.com/knowledge-catalog/docs/reference/rest/v1/projects.locations/lookupContext.md.txt)
  provides a single endpoint for grounding AI agents with contextual metadata.
  It returns a concise, pre-formatted package of metadata, including related
  data assets.

## Locations

You can use data relationships in all
[BigQuery locations](https://docs.cloud.google.com/bigquery/docs/locations.md.txt).

## Limitations

- Knowledge Catalog analyzes a sample of query history to identify relationships, which means that some queries might not lead to link discovery.
- Relationship discovery might take up to 72 hours after the query is executed.

## What's next

- Learn how to [use Knowledge Catalog with MCP, Gemini, and other agents](https://docs.cloud.google.com/knowledge-catalog/docs/pre-built-tools-with-mcp-toolbox.md.txt).