Key takeaways
- For PI System users, TDengine EAI provides a familiar way to browse assets, retrieve time-series data, and refresh Excel reports without leaving the spreadsheet.
- The TDengine Historian Excel Add-In (EAI) brings real-time values, historical data, calculated results, events, and asset metadata directly into Excel.
- It keeps Excel as the user interface while pushing heavy queries and calculations to the Historian backend.
- The Add-In is designed for TDengine Historian environments. Users running only the open-source TDengine TSDB should confirm whether their deployment includes the Historian capabilities required by the Excel Add-In.
Industrial data analysis in Excel with the TDengine Historian Excel Add-In
If you’ve used PI DataLink, you already understand TDengine EAI
PI DataLink has been part of industrial Excel workflows for decades. For many process engineers, operations analysts, and maintenance teams, it is simply the way historian data gets into a spreadsheet: open a workbook, use the add-in task pane, search for the tag or AF attribute, choose a function such as Current Value, Archive Value, Sampled Data, or Calculated Data, set the time range and interval, and refresh the report when the next shift, week, or month arrives.
TDengine Historian Excel Add-In (EAI) is built around the same mental model. It keeps Excel as the working surface, while TDengine Historian supplies the governed asset context, historical values, events, and server-side calculations behind the scenes.
That matters because the familiar Excel historian workflow usually appears in a few recurring situations:
- Recurring operating reports: Monday morning equipment summaries, end-of-shift production numbers, and monthly KPI workbooks can be built once and refreshed on schedule.
- Ad hoc trend checks: when someone notices an abnormal operating condition, engineers can search for the relevant signals, pull the right time range and resolution, and chart the data in Excel without waiting for a CSV export.
- Event-based investigation: breaker trips, batch starts, shutdowns, and maintenance windows can be analyzed by pulling sensor data before and after the event and comparing similar events side by side.
- Energy and utility tracking: meter readings can be brought into Excel for consumption trends, waste analysis, and periodic usage summaries instead of being collected and reorganized manually.
None of these workflows should require code, manual exports, or reformatting data from one system before it can be analyzed in another. That is the core value of a historian Excel add-in, and it is the reason the PI DataLink pattern remains so recognizable.
The migration context
Industrial teams evaluating a move from PI System to TDengine Historian often ask a practical question early: “What happens to our Excel workflows?”
TDengine EAI was built for that question. It uses familiar historian add-in concepts: a task pane, an asset browser, time-range configuration, function categories, and a refresh/update action. The workflow is intentionally straightforward: browse the asset tree, select attributes, set the time range and interval, and apply the query.
For users who already understand PI DataLink, the goal is not to teach a new reporting method from scratch, but to let them carry their spreadsheet-based analysis habits into a TDengine Historian environment.
For organizations already using TDengine Historian, or evaluating it as part of a PI System migration, the Excel Add-In helps protect one of the most ingrained operating workflows: open Excel, refresh the report, and continue the analysis with governed historian data.
Background
In many industrial scenarios, Excel remains one of the most frequently used data analysis tools. Report generation, data verification, trend analysis, and periodic summaries often end up in Excel. The real bottleneck is not whether Excel can compute, but whether data can be obtained reliably and repeatedly. When the analysis targets long-running equipment and systems, with data continuously accumulating and time spans stretching longer, relying on export, copy, and manual organization is not only tedious but also makes consistency and traceability hard to maintain.
Historian and Excel Add-in: their respective roles
TDengine Historian is an AI-powered data historian that combines TDengine TSDB and TDengine IDMP to provide industrial time-series storage, data management, contextualization, analytics, visualization, events, and AI-driven insights.
It organizes device and sensor data in a tree hierarchy, builds a data catalog, completes data contextualization and data standardization, and provides real-time analysis, visualization, event management, and alerting capabilities. On this foundation, Historian introduces the Zero Query Intelligence mechanism, which automatically generates real-time analysis dashboards for each application scenario.
The TDengine Historian EAI, on the other hand, is designed for business users, bringing this already-organized and governed data into Excel so users can perform analysis in their familiar environment without switching systems.
Core features
The core value of TDengine Historian EAI is enabling data to be used efficiently and continuously in Excel. Key capabilities include:
- Complete data retrieval support: element attributes, real-time data, historical archived data, and trend data
- Flexible multi-dimensional data operations: rich query commands supporting complex calculations and filtering
- Functional task pane: multi-entry triggering, intelligent input matching with Excel usage habits
- Users can invoke functions via buttons or right-click menus, and can directly reference cell content for parameter configuration
Five categories of core commands
- Single value query: quickly obtain the status of a device or tag at a specific point in time
- Multi-value query: analyze trend changes over a period
- Calculation and filtering: perform complex statistics on the server side
- Event search: locate key events within massive datasets
- Attribute viewing: view attributes and asset information
- Data setting and updating: update Historian data to the current Excel worksheet
Technical architecture
TDengine Historian EAI adopts a layered architecture:
- User side: provides entry points and a task pane, handling parameter input, validation, and query configuration
- Interface layer: unified API for communication with the Historian backend services
- Data processing layer: performs unit conversion and format standardization on returned data
- Network communication layer: HTTPS ensures data transmission security
TDengine Historian Excel Add-In vs. Traditional Historian Excel Add-Ins
| Dimension | TDengine Historian Excel Add-In | Traditional historian Excel add-ins |
|---|---|---|
| Excel workflow | Preserves the familiar historian-to-Excel pattern: browse assets, select attributes, define a time range, and refresh results in the workbook. | Usually follows a similar add-in pattern, which is why many PI DataLink users can understand the workflow quickly. |
| Computation model | Pushes queries and calculations to the Historian backend, then returns results to Excel. | Often pulls large datasets into Excel first and calculates locally, which can slow down large historical analyses. |
| Data standardization | Uses Historian and IDMP contextualization to support consistent units, names, and asset attributes. | Often requires extra configuration, naming rules, or manual cleanup to keep reports consistent. |
| Architecture | Connects to TDengine Historian over HTTPS and fits cloud or hybrid data historian deployments. | Often depends on Windows desktop components, local clients, or legacy connectors. |
| Data scope | Retrieves current values, historical data, aggregated results, events, and asset metadata directly in Excel. | Typically focuses on tag or historian data retrieval, with broader context depending on the historian setup. |
| Excel user access | Available to all TDengine Historian users, reducing the need for separate manual export processes. | Often packaged as a paid add-on or tied to specific historian client licenses. |
Server-side calculation with the TDengine Historian Excel Add-In
The core innovation lies in the “parsing and computation separation” design. Formulas and query expressions written in Excel are parsed and validated locally, while the actual computation is offloaded to the TDengine TSDB. Queries are pushed down to the database, where aggregation, filtering, and complex calculations are performed at the data source, avoiding repeated data transfer between client and server. This approach supports query analysis of tens of billions of historical data records while preserving the Excel user experience.
Implementation path
TDengine Historian EAI provides guidance on environment preparation, Add-In installation, SDK development, data model design, permission management, and automation scripts. Official technical documentation: https://idmpdocs.tdengine.com/excel-add-in/
Summary
The TDengine Historian Excel Add-In connects daily Excel workflows with governed industrial data. By reducing manual exports, supporting server-side calculation, and making contextualized data available in a familiar tool, it helps business users turn operational data into repeatable analysis and decisions.
