Let's take a look at a few sample prompts to help you get started on your Data Governance and Catalog data exploration journey in CLAIRE GPT.
Data preview of an asset
To preview source data of an asset, orders, you can enter the following prompt: Show data preview of @orders
The following image shows the response of CLAIRE GPT to the prompt, displaying a sample data preview of the orders table:
You can't view data preview for the business name associated with the asset. You can view data preview of the actual asset, such as a table, a view, or an external table. After CLAIRE GPT generates a response for the data preview prompt, you can ask additional questions that include business descriptions added for the asset in Data Governance and Catalog.
You can't view data preview of tables, databases, and schemas with names that contain special characters. You can view data preview of tables that include columns with names that contain special characters except the following characters:
•:
•\
•~
•.
To see the SQL code used to fetch the sample data, click Explanation.
The following image shows the SQL code used to fetch the sample data from the orders table:
Additionally, you can copy the code for further analysis.
To save the sample data in a CSV file for future reference, click the Download icon.
If you refresh the browser or log out of CLAIRE GPT, the sample data will no longer be visible in the conversation, and you will be unable to download it.
The following image shows the response of CLAIRE GPT to the prompt, displaying a data preview of the orders table after a browser refresh:
Identify staff members who managed stores
To identify staff members who managed stores located in London or Santa Cruz, you can enter the following prompt: Identify the staff members who managed stores located in London or Santa Cruz
The following image shows the response of CLAIRE GPT to the prompt, displaying the staff members who managed stores located in London or Santa Cruz:
To see the SQL code used to fetch the sample data, click Explanation.
The following image shows the SQL code with JOIN clause used to fetch the staff members who managed stores located in London or Santa Cruz:
Note: CLAIRE GPT includes regular expressions in the SQL code to improve the accuracy and speed of data exploration responses.
