Options for time series data visualizations with multiple metrics

  • Release version: Australia
  • Updated March 12, 2026
  • 2 minutes to read
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    Summary of Options for Time Series Data Visualizations with Multiple Metrics

    This guide provides insights into effectively visualizing multiple metrics in time series data. It covers customization options such as grouping, visualization types, and Y-axis settings for enhanced clarity and usability in your dashboards.

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    Key Features

    • Separate Visualizations: You can create distinct visualizations for each metric when using multiple data sources, allowing for easier readability.
    • Multiple Y-Axes: If metrics have varying ranges, separate Y-axis scales can be implemented to improve readability. Use this feature judiciously and provide clear labels for each axis.
    • Group By Settings: Separate group-by values can be established for each metric, facilitating tailored data breakdowns. A maximum of three metrics allows for alternative group-bys.
    • Filter Application: The Follow filters feature lets you control filter application for each metric individually, enabling customized dashboard interactions.

    Key Outcomes

    By utilizing these options, ServiceNow customers can create clear, effective time series visualizations tailored to their specific metrics, improving data interpretation and decision-making processes. This flexibility ensures that dashboards can convey complex data relationships in an accessible manner, enhancing user experience and data analysis efficiency.

    If you are showing multiple metrics in a time series data visualization, you can set the group by, visualization type, and Y-axis scale for each metric. You can also have filters on a dashboard apply only to specific metrics.

    Note:
    Additional data sources must use the same unit as the first metric. Otherwise, only the first metric is used in the visualization.

    Separate visualization for each metric

    When you have a data visualization with more than one data source, you have a separate metric for each data source. In time series data visualizations, you can select a separate visualization type for each metric, to make the visualization easier to read. In each Metric tile, selecting the visualization icon opens a list of visualization types to choose from.
    Metrics tile when there are 2 metrics, showing visualization selection menu.
    Note:
    When a Data snapshots indicator is selected, the Metrics component is the same as the source table.

    Dot-walk fields are limited to those fields defined in the snapshot indicator's source.

    Multiple Y-axes

    In some time series, the difference between the range of values of metrics makes it difficult to read the metrics when they share the same Y-axis scale. In this case, you can have separate Y-axis scales for the metric. Add a Y-axis for a metric by selecting the More options icon in the metric tile. Be sparing with this function, however, because having too many Y-axis scales also makes the visualization difficult to read. Also, be sure to give a short but clear label for each Y-axis if you have more than one.
    Adding Y-axis visualizations for each metric.

    Group by per metric

    You can also set separate group-by values for each metric.
    Dialog setting different breakdowns for two different indicators as group-bys.
    If you have no more than three metrics, you can also set alternative group-bys. You can select any field or breakdown that can apply to any of your metrics. The dialog where you select the alternative group-bys says how many of your selections apply to each metric. In runtime, the viewer can select a group-by for each metric, but only from the choices that can apply to that metric.
    Selecting alternative group-bys for two metrics.

    Follow filters per metric

    If Follow filters is activated on a time series or bar visualization that shows multiple metrics, the configuration panel shows an expandable item called Follow filters per metric. Expand this item to toggle filter following on or off for each metric.

    For example, consider a bar visualization that shows the Number of open problems and the Average age of open problems. You can configure this visualization so that the Number of open problems follows any applicable filters on a dashboard, but the Average age of problems does not.
    Bar visualization configured so that of two metrics, one follows filters on a dashboard and one does not.