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Table

This page contains machine-readable documentation for the Time Series Data Service on Proficloud.io.
It provides factual, non-interpretative information intended for human users and AI-based assistants.
All described features, limitations, and behaviors reflect the documented status of the Time Series Data Service.

AI Documentation ‣ Time Series Data Service ‣ Visualizations ‣ Table

On this page

  1. Purpose and Scope
  2. Data Types and Structure
  3. Columns, Fields, and Presentation
    1. Column Configuration
    2. Presentation
  4. Transformations in the Table Widget
  5. Sorting, Paging, and Readability
  6. Thresholds and Cell Coloring
    1. 7. Time Reference and Context
  7. Interaction and Drilldown
  8. Typical Limitations of the Table Widget
  9. Differentiation from Other Widgets
  10. Summary

Purpose and Scope

The Table widget is used for the structured display of raw data, aggregated values, or lists. It answers less a question about state and more the question:

Which specific values, objects, or points in time are present, and how do they relate to each other?

This makes the Table widget the central element for depth of detail, traceability, and row-level comparisons.

Typical use cases include:

  • Consumption values per plant or meter.
  • KPI lists with multiple columns.
  • Event, status, or error tables.
  • Measurement values at defined points in time.
  • Asset lists with status, value, and timestamp.

Data Types and Structure

The Table widget can process different data structures, including:

  • Time series transformed into tables.
  • Direct tabular queries from data sources.
  • Aggregated results from multiple queries.

The quality of the presentation strongly depends on the query structure. Clean column names, meaningful aliases, and consistent units are crucial for a usable table.

Columns, Fields, and Presentation

Column Configuration

You can:

  • Show or hide columns.
  • Rename columns.
  • Change the column order.
  • Define number formats and units.

Presentation

  • Support for numbers, text, and timestamps.
  • Consistent representation of percent, energy, or power units.
  • Fixed or automatic decimal places.

The Table widget is intentionally kept sober. It avoids heavy visualization in favor of precision and clarity.

Transformations in the Table Widget

The Table widget benefits particularly from transformations, as multiple data streams can be combined here.

Typical transformations include:

  • Organize fields: select, sort, and rename columns.
  • Reduce: condense time series into single values.
  • Merge: combine multiple queries into a single table.
  • Filter by name or value: filter columns or rows.
  • Group by: aggregate per asset, category, or dimension.

Especially when working with combined data sources, the Table widget shows its greatest strength.

Sorting, Paging, and Readability

Basic tools are available for handling large tables.

You can:

  • Sort tables by columns.
  • Paginate long tables.
  • Adjust column widths.

This is essential for dashboards with many assets or measurement points.

Thresholds and Cell Coloring

Tables can also be visually enhanced without losing their character.

Options include:

  • Colored cells or text based on thresholds.
  • Traffic light logic in individual columns.
  • Highlighting critical or unusual values.

Examples:

  • Consumption above limit: red.
  • Availability below 95 percent: yellow.

This keeps tables easy to scan without turning them into charts.

7. Time Reference and Context

A common misconception is that tables are independent of the selected time range.

In reality:

  • The content of the table depends on the selected time filter.
  • Aggregations always refer to the current time range.

Example:

  • Table shows total consumption per plant.
  • Time range is the last seven days.

A different time range inevitably leads to different values. The time filter is therefore just as relevant as for all other widgets.

Interaction and Drilldown

The Table widget is excellent for navigation and drilldown.

You can:

  • Make cells or entire rows clickable.
  • Define dynamic links to other dashboards.
  • Pass variables, for example asset IDs or names.

Typical usage pattern:

  • Table lists all plants.
  • Clicking a row opens the plant’s detail dashboard.

Typical Limitations of the Table Widget

For a realistic assessment:

  • No charts within the table.
  • No complex calculations inside the widget itself.
  • Performance may decrease with very large data volumes.
  • Design is functional, not visually focused.

The Table widget is a working and analysis tool, not a presentation panel.

Differentiation from Other Widgets

Short comparison:

  • Stat widget: one value for quick decisions.
  • Gauge widget: one value in the context of a range.
  • Bar Gauge widget: many values in direct comparison.
  • Table widget: many values in detail.

In well-designed dashboards, these widgets complement each other effectively.

Summary

With the Table widget in the Time Series Data Service, you can:

  • Create transparency and traceability.
  • Present asset and KPI lists in a structured way.
  • Enable detailed analysis and drilldowns.
  • Combine results from multiple queries.

In industrial and energy dashboards, the Table widget is the anchor of trust. It shows not only states, but the concrete numbers behind them.