Create Chart

Lakehousecat's chart creation process leverages interactions with linked Custom Models to automatically generate insightful visualizations. This guide outlines how to set up and utilize this feature for enhanced analytics.

Prerequisites

Before generating charts with Lakehousecat, ensure the following prerequisites are met:

1. Registration of Data Sources: Structured and semi-structured data sources must be registered within the system to provide a basis for analysis.

2. Provider Models Registration: Ensure that Provider Models are registered to facilitate advanced query handling and data processing.

3. Custom Models Configuration: Custom Models must be configured appropriately to be linked with the registered data sources. This configuration enables the models to interpret data effectively and generate relevant charts.

Chart Generation Process

Once the prerequisites are satisfied, users can interact with Custom Models in a chat context to inquire about analytical insights. The system may automatically generate visualizations in response to these queries when necessary.

Accessing Charts

Generated charts are accessible within the chat history, providing users with immediate insight into the analysis results. For further access, follow these steps:

1. Open Workspace: Navigate to your Lakehousecat workspace.

2. Go to Analytics: Click on the 'Analytics' section where chart-related features are available.

3. Select Charts: Choose the relevant chart from the list to view and analyze it.

Chart Management

Within Lakehousecat, users have several options to manage generated charts:

• View: Examine the details of the charts to gain insights into the data.
• Share: Distribute charts with other team members or stakeholders for collaborative purposes.
• Edit: Modify chart parameters or data points to refine the visualization.
• Clone: Duplicate charts for parallel analyses or alternate explorations.
• Approve: Confirm the accuracy and relevancy of the charts, marking them as trusted data representations.

Additionally, users with Admin or Builder roles can designate charts as training charts to enhance system performance and analytical preciseness.

Best Practices

• Data Accuracy: Ensure data sources are correctly registered and linked to Custom Models to maintain chart accuracy.
• Collaboration: Utilize sharing features for collaborative data analysis and interpretation.
• Continuous Review: Regularly review and approve charts to keep data insights current and reliable.

Troubleshooting

If issues arise during the chart creation or viewing process:

• Data Source Errors: Verify data source registration to ensure seamless data flow.
• Model Configuration: Review Custom Model configurations to confirm proper linkage and functionality.
• Access Issues: Ensure appropriate permissions within the workspace to access and manage charts.

By adhering to these guidelines, users can maximize the utility of Lakehousecat's chart creation features, driving impactful data-driven decisions.