Converse with Looker dashboard data

Conversational Analytics, powered by Gemini for Google Cloud, lets you investigate your data by asking questions about it in conversational language through an intuitive chat interface. When you start a conversation with a dashboard, Conversational Analytics creates a dashboard data agent automatically, which you can then customize with context and instructions that are specific to your dashboard data.

Before you begin

Before you can use Conversational Analytics to engage with your Explore data, make sure that the setup and requirements for your Looker instance have been satisfied and that you have been granted the appropriate permissions to perform the tasks that are described on this page.

Start a conversation from within a Looker dashboard

Conversational Analytics handles conversations with a single dashboard a little differently from how it handles conversations with a single Explore. With Explores, Conversational Analytics provides the option to chat directly with a single Explore as a one-off conversation or to chat with a data agent that is connected to as many as five Explores and has been provided with additional information and context. When you start a "conversation" with a dashboard, Conversational Analytics creates a data agent that is connected to the dashboard.

To start a conversation with a dashboard data agent, navigate to the dashboard and select spark Chat with this dashboard.

Once you have created a conversation, you can ask questions about the data in the Ask a question field within the conversation. To access your recent conversations with the dashboard agent, select more_vert Menu > Recent conversations.

In addition to asking your dashboard data agent question about the data on the dashboard or in its underlying Explores, you can modify the agent's configuration to customize it with additional context and instructions.

Conversation metadata

The Chat with this dashboard pane includes the following features:

  • To ask a question about the dashboard data, enter a question in the Ask a question field.
  • To edit information about the dashboard agent, select tune Manage agent. In the Editor tab, you can enter agent instructions. Select Update to save your changes to the dashboard agent. Use the Preview tab to preview your changes to the dashboard agent.
  • To expand the dashboard agent conversation pane, select open_in_full View full screen.
  • To access your recent conversations with the dashboard agent, select more_vert Menu > Recent conversations.
  • By default, conversations will be named based on your initial question. To rename a conversation, select a conversation from the Recent conversations menu option, select more_vert, and then select edit Rename.
  • To delete a conversation with a data agent, select more_vert Menu > delete Trash.

Modify your dashboard data agent

To edit information about the dashboard agent, select tune Manage agent. In the Editor tab, you can enter agent instructions. Instructions provide context to help Conversational Analytics understand how to interact with your data and provide accurate and relevant responses. Select Update to save your changes to the dashboard agent. Use the Preview tab to preview your changes to the dashboard agent.

Write agent instructions

You can add free-form instructions that define your data agent's core behavior and provide it with foundational context to consider before processing a user's prompt.

Here are some examples of the types of context that you can provide in the Instructions field:

  • Key fields: The most important fields for analysis
  • Excluded fields: Fields that the data agent should avoid
  • Filtering and grouping: Fields that the agent should use to filter and group data
  • Golden queries: Pairs of natural language questions and their corresponding Explore queries
  • Persona: A role or expertise, character, or tone that you assign to the agent

For tips and best practices for writing agent instructions, see the Best practices for configuring Conversational Analytics in Looker.

Multi-turn conversations

Conversational Analytics will take previous questions and answers into account as you continue the conversation. You can take previous answers and build on them by further refining results or changing the visualization type.

For more guidance on creating questions, see Limitations on questions.

Manage queries within a conversation

When you converse with data, you can manage the conversation by stopping an active query response while it is running or by deleting the most recent question and its response.

Delete the most recent question

To delete the most recent question and its response, follow these steps:

  1. Hold your cursor over the most recent question, and then click Delete message.
  2. In the Permanently delete message? dialog, click Delete to permanently delete the question and its response.

Understand query results and calculations

Conversational Analytics provides details about how your query was interpreted.

Determine how your query was interpreted

If you use Thinking mode to ask your question, you can see how Conversational Analytics reasoned through your query. To see its reasoning, expand the Show thinking option. To hide its reasoning, click Hide thinking.

Conversational Analytics analyzes each query and thinks about how to respond, using the keywords from your query to infer the relevant dimensions, measures, and other parameters from the semantic layer of the conversation's associated datasets and interpreting from your query what aggregations may need to be performed. When you expand Show reasoning, Conversational Analytics displays a plain text explanation of the steps that it took to interpret your query. The explanation also includes the duration that Conversational Analytics thought about the query.

Manage conversations

Each conversation remains in the Recent conversations section the dashboard conversation more_vert Menu. You can change the names of conversations, delete conversations, or restore them from the trash folder.

  • To access your recent conversations with the dashboard agent, select more_vert Menu > Recent conversations.
  • By default, conversations will be named based on your initial question. To rename a conversation, select a conversation from the Recent conversations menu option, select more_vert, and then select edit Rename.
  • To delete a conversation with a data agent, select more_vert Menu > delete Trash.

Delete a conversation

To delete a conversation with a data agent, select the conversation's more_vert three-dot menu, and then select delete Delete.

Restore or permanently delete a conversation

To restore or permanently delete a conversation from the trash, follow these steps:

  1. Select more_vert Menu > delete Trash.

  2. In the Trash pane, find the conversation that you want to restore or permanently delete. Select the conversation's more_vert three-dot menu, and then select one of the following options:

    • Restore: Restores the conversation. The conversation can be accessed from the Recent conversations menu option.
    • Delete Permanently: Permanently deletes the conversation.

Known limitations

Conversational Analytics dashboard data agents have the following known limitations:

  • Advanced Analytics isn't supported for dashboard data agents.
  • Dashboard data agents aren't available for LookML dashboards.
  • Dashboard data agents query the Production Mode of dashboard data
  • Dashboard data agents can't be shared with other users.

Limitations on visualizations

Conversational Analytics leverages Vega-lite for conversation chart generation. The following Vega chart types are fully supported:

  • Line chart (one or more series)
  • Area chart
  • Bar chart (horizontal, vertical, stacked)
  • Scatter plot (one or more groups)
  • Pie chart

The following Vega chart types are supported, but you may encounter unexpected behavior when rendering them:

  • Maps
  • Heatmaps
  • Charts with tooltips

Chart types that exist outside the Vega catalog are not supported. Any charts that are not specified in this section are considered unsupported.

Limitations on data sources

Conversational Analytics has the following data source limitations:

  • Conversational Analytics can return a maximum of 5,000 rows per query.
  • Conversational Analytics cannot set the value of a filter-only field that is defined using the LookML parameter or filter parameters.

Limitations on questions

Conversational Analytics supports questions that can be answered by a single visualization, for example:

  • Metric trends over time
  • Breakdown or distribution of a metric by dimension
  • Unique values for one or more dimensions
  • Single metric values
  • The top dimension values by metric

Conversational Analytics doesn't yet support questions that can only be answered with the following types of complicated visualizations:

  • Prediction and forecasting
  • Advanced statistical analysis, including correlation and anomaly detection