Use BigQuery data with Conversational Analytics

With Conversational Analytics in Looker Studio, you can start a conversation directly with a BigQuery table or with a data agent that is built with a BigQuery table.

This page guides you through the following processes:

Learn how and when Gemini for Google Cloud uses your data. As an early-stage technology, Gemini for Google Cloud products can generate output that seems plausible but is factually incorrect. We recommend that you validate all output from Gemini for Google Cloud products before you use it. For more information, see Gemini for Google Cloud and responsible AI.

Before you begin

To use Conversational Analytics in Looker Studio, you must meet the following requirements:

  1. You must be a user under a Looker Studio Pro subscription. Looker Studio Pro licenses are available at no cost to Looker users.
  2. An administrator must have enabled Gemini in Looker for Looker Studio.

To use BigQuery data with Conversational Analytics, ensure that you have the following BigQuery Identity and Access Management (IAM) roles and permissions:

  • The bigquery.jobs.create IAM permission on the billing project
  • The roles/bigquery.dataViewer IAM role on the project, dataset, or table that is being queried

Use a BigQuery table as a data source

You can connect to a BigQuery table as a data source for Conversational Analytics in Looker Studio. BigQuery data sources appear in the list of available data sources on the Chat with your data page. To use a BigQuery table as a data source with Conversational Analytics, follow these steps:

  1. In Looker Studio, navigate to Conversational Analytics.
  2. On the Chat with your data page, select the Data sources tab.
  3. Select Connect to data, and then select BigQuery from the drop-down menu.

  4. In the Select data window, select one of the following tabs to connect to a BigQuery dataset or to browse public datasets.

    • Recent Projects: Lists the BigQuery projects that you accessed most recently.
    • All Projects: Lists all the BigQuery projects that you have access to.
    • Public Datasets: Lists BigQuery public datasets.
    • Enter Project ID: Lets you specify the unique project ID for a specific project.

  5. Select a BigQuery project in the Recent Projects or All Projects tab, or enter a project ID in the Enter Project ID tab. Optionally, use the Search Projects search bar to filter the list. (If you're connecting to a public dataset, proceed to the next step.)

  6. The Select data window displays the Datasets tab, or it displays Public Datasets if you're connecting to a public dataset. Select a BigQuery dataset. Optionally, use the Search Datasets search bar to filter the list.

  7. The Select data window displays the Table tab. Select the table that you want to connect to in the Table tab. Optionally, use the Search Tables search bar to filter the list.

  8. Click Connect.

Converse with BigQuery data

Once you have connected to a BigQuery data source, you can ask questions about your BigQuery data.

When you converse with your data, the collapsible Data panel shows the name of the BigQuery table that the conversation is using. The Data panel panel also provides the following options:

  • View fields: View the table in BigQuery in a new browser tab.
  • New conversation: Start a new conversation with the BigQuery data that the current conversation is using.

Ask a question

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:

  • Percent change of a metric over time, including period-over-period analysis
  • Prediction and forecasting
  • Advanced statistical analysis, including correlation and anomaly detection

Visualizations

If the response to your query includes a visualization, the result shows the following tabs:

  • Chart: Shows the rendered visualization.
  • Table: Shows the underlying data table. You can change the data table sort order by clicking on the Sort by arrows next to the column names. Changing the sort order of the table columns won't alter the visualization.

Determine how an answer was calculated

To see how Conversational Analytics arrived at an answer or created a visualization, click How was this calculated? below the response.

When you click How was this calculated?, Conversational Analytics displays the following tabs:

  • Code: Displays the BigQuery SQL query that was run to generate the result.

  • Text: Provides a plain text explanation of the steps that Conversational Analytics took to arrive at the given answer. This explanation includes the raw field names that were used, the calculations that were done, the filters that were applied, the sort order, and other details.

Supported 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:

  • Percent change of a metric over time, including period-over-period analysis
  • Prediction and forecasting
  • Advanced statistical analysis, including correlation and anomaly detection

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.

Stop a query response

To stop running a query after you've sent a message, click Stop response. Conversational Analytics stops running the query and displays the following message: The query was cancelled.

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.

Known limitations

When you use BigQuery data with Conversational Analytics, you can converse with only one BigQuery table at a time. To converse with a different BigQuery table or with a data agent that uses a different BigQuery table, start a new conversation.

For information about additional limitations, see the documentation on known limitations in Conversational Analytics.