Which BI tools' AI answers follow-up questions?

Quoted from Databricks’s docsEach conversation thread maintains its context, letting you build on previous questions.

Quoted from Snowflake’s docsWhen the report is ready, it stays in context for the rest of the thread, so follow-up questions such as “break that down by region” run as standard chat turns without restarting the research.

Quoted from Omni’s docsIterate on the questions you ask to provide a more refined result. For example:

Quoted from Hex’s docsOf course, users can also ask follow up questions in their threads to tweak results.

Quoted from Sigma’s docsYou can continue to ask follow-up questions to refine your analysis or understanding of the data source.

Quoted from BigQuery’s docsContinues a stateful conversation by sending a chat message that references an existing conversation and its associated agent context.

Quoted from Looker’s docsConversational Analytics will take previous questions and answers into account as you continue the conversation.

Quoted from Tableau’s docsWhen you type a question or request into the conversation pane, a combined prompt consisting of the user's input, metadata describing the current state of the viz (web authoring), or Tableau Prep flow, and historical context from the conversation pane flow through the Einstein Trust Layer to the LLM.

Quoted from Power BI’s docsCopilot also responds to follow-up requests based on what you already asked in your current session.

Quoted from Metabase’s docsMetabot remembers the context of a thread.

Quoted from Alteryx’s docsUpdate the workflow with follow-up requests, such as adding a filter or sorting the results.

Quoted from MotherDuck’s docs- One conversation per Dive. Sessions are scoped to a specific Dive. Each one has its own chat.

Quoted from Mode’s docsOne of the primary benefits of the workflow is the ability to integrate natural language seamlessly into SQL code you've already written to quickly iterate.

Quoted from Redshift’s docsIteratively ask follow-up questions to get more detailed analysis from the assistant.

Quoted from Streamlit’s docs- Finally, we'll Build a ChatGPT-like app that leverages session state to remember conversational context, all within less than 50 lines of code.