Conversational Analytics
A data analysis approach based on natural language dialogue, in which users explore data by conversing with a system rather than relying on pre-built fixed reports. This method is suited to open-ended, exploratory query scenarios, allowing flexible ad hoc investigation of datasets without requiring upfront dashboard or report configuration.
Timeline (last 90 days)
Mature conversational analytics products typically require an accompanying semantic layer that structures and stores business definitions for the model to call.
Conversational analytics hands the choice of definitions to the model to complete automatically, which brings flexibility while also introducing the risk of definition drift.
Conversational analytics tools are suitable for exploratory data analysis, and for key decisions it is still recommended to manually review the definitions and data sources.
Traditional BI tools require analysts to build dashboards and fixed reports in advance, limiting users to viewing data within a predetermined framework, whereas conversational analytics allows users to ask questions in an exploratory, open-ended manner.
All Facts (4)
Mature conversational analytics products typically require an accompanying semantic layer that structures and stores business definitions for the model to call.
50%UnverifiedConversational analytics hands the choice of definitions to the model to complete automatically, which brings flexibility while also introducing the risk of definition drift.
50%UnverifiedConversational analytics tools are suitable for exploratory data analysis, and for key decisions it is still recommended to manually review the definitions and data sources.
50%UnverifiedTraditional BI tools require analysts to build dashboards and fixed reports in advance, limiting users to viewing data within a predetermined framework, whereas conversational analytics allows users to ask questions in an exploratory, open-ended manner.
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