Abstract: System, method, and computer product embodiments are described for querying a database using natural language queries (NLQ) to produce actionable results in an answer card. The method allows a user to take further action with the answer card by editing the card contents, manipulating the way data is displayed, or querying the answer results for more details of the data. By the method, the user may continue exploration of the data, use the results to collaborate with others, or build a story from the data in a presentation format, such as a dashboard, while maintaining access to the real-time data of the database through the answer card. System and computer product embodiments implement the method.

Abstract: Embodiments are described for enabling a user to query a database using natural language and receive results without requiring the user to manipulate or know details of the database contents. The user is guided in the creation of the natural language query by suggested predetermined queries from a template. Natural language is parsed using the template. The approach allows a user's query words to be completed automatically from the template as the user inputs the words. The approach further allows the next suggested parts of the query to be automatically typed from the template ahead of the user's cursor. Other features provide feedback to the user for invalid or irrelevant queries that cannot be parsed, including suggesting complete predetermined queries from the template. The approach helps the user focus the query on exactly what the user seeks to learn from the database without complex, process-intensive parsing.

Abstract: Embodiments are described for enabling a user to query a database using natural language and receive results without requiring the user to manipulate or know details of the database contents. The user is guided in the creation of the natural language query by suggested predetermined queries from a template. Natural language is parsed using the template. The approach allows a user's query words to be completed automatically from the template as the user inputs the words. The approach further allows the next suggested parts of the query to be automatically typed from the template ahead of the user's cursor. Other features provide feedback to the user for invalid or irrelevant queries that cannot be parsed, including suggesting complete predetermined queries from the template. The approach helps the user focus the query on exactly what the user seeks to learn from the database without complex, process-intensive parsing.

Abstract: System, method, and computer product embodiments are described for querying a database using natural language queries (NLQ) to produce actionable results in an answer card. The method allows a user to take further action with the answer card by editing the card contents, manipulating the way data is displayed, or querying the answer results for more details of the data. By the method, the user may continue exploration of the data, use the results to collaborate with others, or build a story from the data in a presentation format, such as a dashboard, while maintaining access to the real-time data of the database through the answer card. System and computer product embodiments implement the method.