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How to Create BI Analysis

Data Source​

Connect to Data Source​

The first step in AI Data is connecting to a data source to provide foundational data for subsequent analysis.

  • Supports connecting to various mainstream data platforms, including MySQL, SQL Server, Azure Databricks, etc.;
  • After adding a data source, you can view all tables in this data source, and users can selectively check the tables they need to use;
  • By default, the system only synchronizes metadata (such as table structure and field information), and does not synchronize actual data records, ensuring data security;
  • Provides a "Test Connection" feature to ensure the connectivity of the data source is correct;

Data Catalog​

Manage Data Catalog​

After connecting to a data source, users can view and manage synchronized tables in the "Data Catalog" module.

  • Only displays checked tables in the data source;
  • Supports viewing each table's table name, business description, field name, and field description;
  • Shows the relationships between this table and other tables, including related tables, related fields, and relationship types (such as primary and foreign keys);
  • Supports one-click "Intelligent Data Knowledge Supplement", where the system uses AI and Schema to automatically generate business aliases and descriptions for tables and fields;
  • Supports the "Data Table Synchronization" feature to reload updated table structures.

Business Domain​

Build Data Model​

To help the system better understand the business relationships between data, you need to build a "Business Domain" to define the logical relationships between tables.

1. Create a New Business Domain​

  • Enter the name of the business domain;
  • Select the referenced data source;
  • After creation, you can enter the business domain management interface.

2. Add Data Tables and Relationship Modeling​

  • Add multiple business-related data tables as "business domain nodes";
  • Each node represents a table, and multiple nodes can be added;
  • Click the "Relationship List" of each table node to add relationships:
    • Set the From field (field in the current table);
    • Set the To table and its field (target table and target field);
    • Select the relationship type: one-to-one, one-to-many, many-to-one, many-to-many;
    • Submit to complete the relationship binding between the two tables.

In this way, users can build a complete data relationship network within the business domain, facilitating subsequent intelligent queries and chart generation.

3. SQL Template Modeling​

  • Supports creating business relationship templates using SQL statements;
  • Templates include natural language questions and corresponding SQL queries;
  • Suitable for configuration by IT administrators, business users can directly use them, lowering the learning curve.

4. Relationship Overview​

  • Presents all tables and their structural relationships within the business domain for global understanding and management.

Intelligent BI​

Intelligent Analysis and Chart Generation​

After building the business domain, users can perform visual analysis in the "Intelligent BI" module.

1. Select Business Domain​

  • After entering Intelligent BI, select an existing business domain;
  • The data tables under this domain will be displayed on the left;
  • Supports data table preview, including field names and sample data.

2. Intelligent Chart Generation​

  • Enter chart requirements in the input box, supports natural language queries, such as:
    • "Sales trend in the last 7 days"
    • "Order volume grouped by region"
  • The system automatically converts the semantic input into SQL queries and generates the corresponding charts;
  • Supports various chart types such as bar charts, line charts, scatter plots, etc.;
  • Optimizes and suggests completions for user input, making it very suitable for business users without technical backgrounds;
  • Charts support editing, including title, chart type, XY axis settings, color style, etc.

3. Data Insight Analysis​

  • On the right side of the BI interface, click "Insight";
  • The system uses AI to automatically analyze data trends, anomalies, and possible causes;
  • Helps users quickly identify key business issues and assist business decision-making.

My Analysis & Analysis Center​

Analysis Publishing and Sharing​

After adjusting the analysis, you can publish and share the analysis.

1. Analysis Publishing​

  • Supports publishing analysis to:
    • My Analysis (visible to individual);
    • Analysis Center (shared within the organization);
  • Supports setting analysis categories during publishing.

2. Analysis Sharing​

  • Supports setting:
    • Whether to enable password protection;
    • Access permissions (preview only);
    • Expiration time limit;
  • Can be quickly shared with others via link.

3. Analysis Management​

  • In "My Analysis", you can edit, rename, share, download, or delete published analyses;
  • "Analysis Center" provides a global analysis summary, supporting category viewing and favorites.

Summary​

Through the process of "Data Source → Data Asset → Business Domain → Intelligent BI → Analysis", the Data module provides users with a complete, efficient, and intelligent data analysis and visualization solution. Users can start by connecting to multiple types of data sources, synchronizing metadata as needed, mastering table structures and field information through the data asset module, and building complex business logic models with the help of business domains to establish semantic connections between data.

In the Intelligent BI module, the system significantly lowers the analysis threshold through natural language recognition, intelligent chart generation, and AI insight analysis capabilities, enabling even non-technical business users to get started quickly. Finally, users can publish, manage, and share generated charts as analyses, supporting internal knowledge sharing and external output within the organization.

Throughout the entire process, the system consistently follows the design philosophy of "low-code, high intelligence, strong integration", balancing ease of use for business users and scalability for professional users, truly realizing a full-chain closed loop from data access, modeling, analysis, insight to decision support, and effectively accelerating the transformation and upgrade of enterprises into data-driven organizations.