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Data Application Scenarios

Practical Tutorial Overview: Intelligent Analysis and Connectivity to Unlock Data Value​

This tutorial focuses on the Data module in the SERVICEME NEXT platform. Through two hands-on cases, it helps users master how to build data-driven intelligent applications with the platform. Whether you want to quickly generate visual reports or create an intelligent Agent with data connectivity and analysis capabilities, this tutorial will provide you with clear guidance and practical methods.

📊 Case 1: Building a BI Analysis Report from Scratch​

This practical case is designed to help users quickly build an intelligent analysis report based on sales data, enabling sales data visualization and natural language insights. Through this tutorial, you will master the following key operations:

  • Import or connect sales data tables (such as Excel, SQL, or third-party systems)
  • Quickly configure data fields, metrics, and dimensions
  • Apply intelligently recommended charts and natural language analysis
  • Publish and share interactive reports

This case is suitable for roles such as marketing operations, sales management, and data analysis, helping users more efficiently gain insights into business trends, evaluate performance indicators, and support decision-making.

🤖 Case 2: Building a Data Agent from Scratch​

This case will guide you in building an intelligent Agent capable of dynamically accessing and querying data sources. Unlike static reports, this Agent can, based on the user's natural language request, connect in real time to designated data sources (such as databases, APIs, or spreadsheets), and return structured results or generate visualized responses.

You will learn how to:

  • Configure data connectors to connect business systems or databases
  • Design the Agent’s data query intents and parameter recognition methods
  • Implement a multi-turn interactive data Q&A workflow
  • Combine chart components to return graphical analysis results

This practice is suitable for building scenarios such as "Sales Data Assistant," "Inventory Query Bot," and "Business Analysis Assistant," significantly improving the intelligence level of data services.

Through learning this module, users can not only "see the data" but also use intelligent Agents to make the data "come alive," transforming complex data queries and business insights into a natural conversational experience and truly unlocking the value of data assets.