Ai-generated data objects for data visualization

A computing apparatus comprising:

• one or more computer readable storage media;
• one or more processors operatively coupled with the one or more computer readable storage media;
• and
• program instructions stored on the one or more computer readable storage media that, when executed by the one or more processors, direct the computing apparatus to at least:
• receive a natural language input from a user relating to a table of data in a data analytics application, wherein the natural language input relates to creating a visualization of the data and wherein the table comprises the data organized according to table columns;
• generate a prompt for a large language model (LLM) service, wherein the prompt includes names of the table columns, wherein the prompt tasks the LLM service with selecting columns of the table columns for the visualization based on the natural language input and the names of the table columns, and wherein the prompt tasks the LLM service with generating a response in a JSON format;
• populate a JSON object according to the response, wherein the JSON object describes the visualization;
• and
• create the visualization based on the JSON object.

One or more computer-readable storage media having program instructions stored thereon that, when executed by one or more processors of a computing device, direct the computing device to at least:

• receive a natural language input from a user relating to a table of data in a data analytics application, wherein the natural language input relates to creating a visualization of the data and wherein the table comprises the data organized according to table columns;
• generate a prompt for a large language model (LLM) service wherein the prompt includes names of the table columns, wherein the prompt tasks the LLM service with selecting columns of the table columns for the visualization based on the natural language input and the names of the table columns, and wherein the prompt tasks the LLM service with generating a response in a JSON format;
• populate a JSON object according to the response, wherein the JSON object describes the visualization;
• and
• create the visualization based on the JSON object.