✨Chat BI
ChatBI is an innovative feature we have introduced that combines chat functionality with Business Intelligence (BI) analytics capabilities. It provides users with a more intuitive and convenient data analysis experience through natural language interactions.
Here are the main features of ChatBI:
Natural Language Querying: Users can ask questions in natural language and receive data analysis results directly, without needing to know complex query languages. This feature makes it easy for non-technical users to gain insights from data.
Multi-Turn Conversations: Supports multi-turn conversation functionality, allowing users to engage in continuous, context-aware interactions. The system remembers previous conversation content, making data analysis more in-depth and accurate.
Support for Various Large Language Models: ChatBI integrates several mainstream large language models, such as ChatGPT and Llama, enhancing the accuracy of natural language understanding and generation to meet diverse business needs and language support.
Real-time Data Analytics: Provides real-time data analysis and visualization capabilities, helping businesses quickly respond to market changes and make decisions.
Data Visualization: Supports various data visualization methods, including pie charts, line charts, and bar charts, helping users intuitively understand data.
Self-Service Analytics: Users can explore and analyze data on their own without relying on technical teams, using drag-and-drop report builders and data exploration tools.
Integration with Multiple Data Sources: Supports connection and integration with data from various sources, such as databases, cloud services, SAP ERP systems, providing users with rich data sources.
Collaboration Features: Supports team collaboration, allowing users to share analysis results, comment, and discuss data insights.
Security and Access Control: Provides stringent data security and access management to ensure the protection of sensitive data.
Mobile Support: Allows access and operations from mobile devices, enabling data queries and analysis anytime, anywhere.
Questions
- Semantic Model Selection: In this section, users can select a semantic model from the available list. Semantic models typically represent different domains or data areas within the system.
- Dataset Selection: Once a semantic model is chosen, users can select a specific cube (dataset) within that model. This step determines which dataset the analysis will draw from.
- Dimensions, Measures, and Metrics: After selecting a cube, click the expand button to open the dataset's details.
- Ask a Question: Enter a question and click send.
Answers
The smart assistant responds to questions with text and graphical answers.
- Data Visualization: Generates visual data representations in response to questions. These visualizations can include bar charts, pie charts, line charts, and other data representations, making it easier for users to interpret and analyze data.
- Explore Button: Users can further explore data by clicking the "Explore" button. This opens the explorer function, allowing for deeper exploration and analysis of the result data, applying exploration findings to the question results. For more details on the explorer function, see the "Explorer" section.
Dashboard Integration
Finally, users can easily add graphical results from their questions to existing Story Dashboards for sharing with teams or reporting.