Using Data Playground
Last updated
Last updated
Data connector playground is a place that we can adjust data connector. The Data Connector Playground serves as a platform for configuring a data connector to suit specific requirements. Within this dynamic environment, users have the flexibility to enhance the performance and capabilities of the connector through two essential functionalities.
The playground facilitates the inclusion of "training" data, a pivotal component for refining and optimizing artificial intelligence (AI) algorithms. By integrating diverse datasets that encapsulate the range of potential inputs the connector may encounter, users can effectively train the AI model embedded within the connector. This process contributes to improved accuracy, efficiency, and adaptability of the data connector, ensuring it can adeptly handle a variety of real-world scenarios.
This serves as your comprehensive guidebook, offering insights and instructions for navigating and enjoying your experience in the Data Connector Playground. Whether you're a novice or an experienced user, these guidelines are designed to enhance your exploration and ensure a seamless and enjoyable journey through the playground of data connectors
In the Feedloop AI platform, navigate the "Resource" tab to manage various resources, including data connectors that we have made before.
In the "Resources" interface, find and click on one of the "Data Connectors" that were made before. In this case we'll click on "qorebase rosma"
There will be two types of tabs displayed on the data connector playground interface. Here, we can choose these tabs based on our needs. Currently, the available tabs are:
Playground
Settings
For now, our focus will be on the Playground tab, which houses features such as adding and modifying training data, SQL generation and modification, and SQL execution.
