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Data model

The data model is the core of Qluent and it builds a picture of your data that is understood by AI. The more accurate the context is the better the Qluent answers will be.

Illustrates adding descriptions to tables and columns in the data model.

Query guidance/instructions​

An open text field to capture supporting information about the project that is used by the AI aspect of Quent.

Use cases​

  • What your project/business does
  • Briefly describe the data that you're connecting
  • Other supporting facts that help better answer questions

An example of this could be:

Qluent is a SaaS that allows users to connect data together so they can ask questions in plain language.
Usage, marketing and sales data is connected.
Today is 2024-11-19

Configure tables​

Tables and columns available to Qluent are listed here. They are automatically detected based on the schema of your connected data source. You can:

  • Enable/disabled each table/column
  • Set a description for each table/column

Use cases​

  • When table/column names are not descriptive. e.g. Table sls24 is difficult to understand therefore adding a description Sales from 2024 would yield more accurate results from Qluent.
  • When multiple tables/columns contain similarly named columns but have different meanings, specify the difference in the description. e.g. Table some_table.col_a and other_table.col_a

Tables/Columns prefixed with underscores e.g. _my_private_table are ignored by default.