Choosing between connectors and data agents
In addition to using direct Data Cloud connectors to query data in plain language, you can also use Conversational Analytics agents to enable these experiences. While Data Cloud connectors allow you to provide exploratory and ad hoc analysis for users, conversational analytics agents are scoped agents that are built and certified directly by data teams within your organization. These can be built across Data Cloud products such as BigQuery, Looker, and operational databases including Spanner, AlloyDB, and Cloud SQL.
These pre-configured agents allow users to run highly governed, multi-step strategic analyses that are scoped to particular subsets of data, supporting compliance requirements and predictable results for reporting. These data agents can also be published in Gemini for consumption or made available via API for building your own conversational apps in the enterprise.
These approaches are complementary. Gemini direct connectivity also surfaces relevant published agents created by central data teams, so users can decide whether to proceed with ad hoc analysis using the connectors or use the scoped agent. You can choose the right approach for each workload.
Built-in access controls and governance
Data Cloud connector queries execute under the end user’s identity. An employee without access to executive salary data or protected healthcare records cannot query that data through natural-language prompts. The agent only discovers metadata in Knowledge Catalog to which you have access, and only executes queries that your account has permission to run.
How to create Data Cloud connectors
Administrators can configure Data Cloud connectors in the Gemini admin console. From there, admins set up default read-only connections to datasets in BigQuery, operational databases, or Looker, with Knowledge Catalog enabled automatically. Once configured, end users can enable the connector in Gemini to start querying data and building reports in plain language.
