Information

When you select a table from the left navigation panel, the following options become available to manage details specific to that table. Each menu item is designed to help you refine how LLMate understands and works with your data at a granular level.

Field-Level Description

• Purpose: Document what each field (column) in the table represents.

• Why It Matters: Clear descriptions ensure that everyone understands the context of each data field, and it helps LLMate interpret queries more accurately.

• Typical Actions:

  • Add or update descriptions for fields to explain their meaning (e.g., “Customer ID is a unique identifier assigned to each customer”).

  • Remove outdated or irrelevant field descriptions.

Sample Values

• Purpose: Provide examples of the data contained in each field.

• Why It Matters: By reviewing sample values, you can verify that data is being interpreted correctly and is clean, which helps in validating data quality and appropriateness for analysis.

• Typical Actions:

  • Review automatically provided sample entries for each field.

  • Update or annotate samples if needed to clarify unusual or complex values.

Cardinality and Data Type

• Purpose: Show how many unique entries each field contains (cardinality) and the type of data stored (e.g., text, number, date).

• Why It Matters: Understanding cardinality and data types helps in optimizing queries, refining AI-generated suggestions, and ensuring accurate calculations and analysis.

• Typical Actions:

  • Verify that the inferred data type matches the actual content.

  • Adjust data type or cardinality settings if inaccuracies are found.

  • Use this information to decide on indexing or indexing strategy for performance improvements.

Fill with AI

Purpose:

This feature helps users generate descriptions for tables and columns automatically using AI. It speeds up the documentation process and ensures consistent metadata for better data understanding.

Why It Matters:

• Saves time by automatically generating meaningful descriptions.

• Ensures consistency across table and column documentation.

• Helps users quickly understand the purpose of different data points.

Query

Users can manually enter a prompt to refine the AI-generated description. If needed, they can enable Auto-fill to replace existing descriptions with newly generated ones.

Typical Actions

1. Edit Descriptions: Click on the "Edit" button to update descriptions for the table and columns.

2. Use Fill with AI: Click "Fill with AI" to open the AI-powered description generator.

1. Select Model & Provider: Choose an AI model (e.g., OpenAI) to generate descriptions.

1. Enter Prompt (Optional): Provide a custom prompt for a more tailored description.

1. Generate: Click Generate, to generate the AI-generated descriptions.

The table and column descriptions will be added automatically and modify if needed.

This feature enhances documentation efficiency and ensures that data definitions are clearly outlined for better usability.