TDengine IDMP User Manual
TDengine IDMP (Industrial Data Management Platform) is an AI-native industrial data management platform designed for managing, contextualizing, standardizing, visualizing, analyzing, and deriving intelligence from industrial data collected from sensors, devices and equipment.
This manual is the complete user guide for TDengine IDMP, covering everything from core concepts to system administration. The reading guidance below will help you find the most effective path for your role.
If you only want a quick overview of what IDMP is, reading Chapter 1 — Introduction is sufficient. Regardless of your role, we recommend everyone read the core concepts section in Chapter 1 carefully. The element is the fundamental building block of the entire platform, and understanding it is a prerequisite for using any feature.
If you are a business manager or operations staff member who primarily needs to view panels and events, focus on Chapter 4 (Visualization and Dashboards) and Chapter 6 (Events). You can skip the sections on creating and configuring panels and analyses. We also strongly recommend trying the AI features in Chapter 8 — you can ask questions about your operational data in plain language without any technical background.
If you are a process engineer or data analyst who needs to build monitoring systems and configure analysis rules, read Chapter 3 (Industrial Data Modeling), Chapter 4 (Visualization and Dashboards), Chapter 6 (Events), Chapter 7 (Real-Time Analysis), and Chapter 8 (AI-Powered Insights) systematically. Data modeling is the foundation of everything — the richer your model, the higher the quality of your visualizations, analyses, and AI insights. Chapter 16 (Best Practices) is also worth reading.
If you are a system administrator responsible for deployment, user management, and system maintenance, focus on Chapter 2 (Getting Started, which includes installation and deployment), Chapter 12 (Data Ingestion), Chapter 14 (Administration, covering users and roles, system configuration, backup and restore), and Chapter 15 (Integrating with Other Systems). When issues arise, Chapter 18 (Troubleshooting) will be your reference.
If you are an OT/IT integration engineer connecting existing industrial systems to IDMP, focus on Chapter 1 Sections 1.3 and 1.4 (TDengine architecture and the relationship between IDMP and TSDB), Chapter 3 (data model design, analogous to PI Asset Framework), Chapter 12 (Data Ingestion), Chapter 13 (Libraries, including units of measure and enumeration sets), and Chapter 15 (APIs and integration methods).
IDMP is designed with the philosophy that users should be able to get started without reading a manual. Most features are self-explanatory in the interface, so this manual focuses on conceptual explanations and advanced configuration rather than button-by-button walkthroughs. When in doubt, use the AI features directly in the application — ask any question in natural language and get answers grounded in your actual data.
Regardless of your role, we invite you to explore the zero query intelligence and Chat BI capabilities. They lower the barrier to industrial analytics to zero, so anyone can unlock business value from collected data at any time — letting the data speak for itself.
If you find any errors or unclear descriptions, click "Edit this page" at the bottom of any page to submit a correction directly.
Together, we make a difference.
