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Copilot for Real-Time Intelligence (preview)

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Copilot for Real-Time Intelligence is an advanced AI tool designed to help you explore your data and extract valuable insights. You can input questions about your data, which are then automatically translated into Kusto Query Language (KQL) queries. Copilot streamlines the process of analyzing data for both experienced KQL users and citizen data scientists.

Important

This feature is in preview.

Prerequisites

Note

Capabilities of Copilot for Real-Time Intelligence

Copilot for Real-Time Intelligence lets you effortlessly translate natural language queries into Kusto Query Language (KQL). The copilot acts as a bridge between everyday language and KQL's technical intricacies, and in doing so removes adoption barriers for citizen data scientists. By harnessing OpenAI's advanced language understanding, this feature allows you to submit business questions in a familiar, natural language format, which are then converted into KQL queries. Copilot accelerates productivity by simplifying the query creation process with a user-friendly and efficient approach to data analysis.

Access the Real-Time Intelligence Copilot

  1. To access Copilot for Real-Time Intelligence, navigate to a new or existing KQL queryset.
  2. Connect to a database. For more information, see Select a database
  3. Select the Copilot button.
  4. In the Copilot pane, enter your business question in natural language.
  5. Press Enter. After a few seconds, Copilot will generate a KQL query based on your input. You can copy the query to the clipboard, or insert it directly in the KQL query editor. To run the query in the query editor, you must have write access to the KQL queryset.
  6. Select the Run button to execute the query.

Note

  • Copilot doesn't generate control commands.
  • Copilot doesn't automatically run the generated KQL query. Users are advised to run the queries at their own discretion.

You can continue to ask questions and generate queries in the Copilot pane, but each question is evaluated separately and not connected to previous questions or their answers.

Improve the accuracy of Copilot for Real-Time Intelligence

Here are some tips that can help improve the accuracy of the KQL queries generated by Copilot:

  • Start with simple natural language prompts, to learn the current capabilities and limitations. Then, gradually proceed to more complex prompts.
  • State the task precisely, and avoid ambiguity. Imaging you shared the natural language prompt with few KQL experts from your team without adding oral instructions - would they be able to generate the correct query?
  • Supply any relevant information that can help the model to generate the most accurate query. If you can, specify tables, operators or functions that are critical to the query.
  • Prepare your database: Add docstring properties to describe common tables and columns. This might be redundant for descriptive names (for example, timestamp) but is critical to describe tables or columns with meaningless names. You don't have to add docstring to tables or columns that are rarely used. For more information, see .alter table column-docstrings command.

Limitations

Complex and long user input might be misunderstood by Copilot, resulting in potentially inaccurate or misleading suggested KQL queries. User input that directs to database entities that aren't KQL Database tables or materialized views (for example KQL function), may result in potentially inaccurate or misleading suggested KQL queries. More than 10,000 concurrent users within an org will probably fail or result in major performance hit.

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