Time series visualization example
Summarize
Summary of Time Series Visualization Example
This guide provides a step-by-step example of creating time series visualizations in ServiceNow, illustrating how to track and compare incident data over time. The focus is on utilizing a single data source initially and gradually adding complexity for enhanced insights.
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Key Features
- Data Source Selection: Start by selecting the "Number of open incidents" indicator from suggested data sources.
- Real-Time Configuration: Utilize the Configuration panel to adjust visualizations, including setting date ranges and viewing trends.
- Grouping Data: Group incidents by priority, allowing for separate lines for each group in the visualization.
- Multiple Indicators: Add the "Number of new incidents" indicator for comparative analysis within the same visualization.
- Visualization Types: Change visualization types (e.g., from line to column) and customize metrics individually, including setting different Y-axes.
- Legibility Enhancements: Improve the readability of legends and other display elements for better viewer comprehension.
Key Outcomes
By following this example, ServiceNow customers can create informative time series visualizations that effectively communicate trends and comparisons in incident data. After saving the visualization, it can be added to dashboards or stored in the Data Visualizations library for shared use among dashboard designers, facilitating collaborative insights across the organization.
Time series visualizations show the changes in data over time. This example starts with a single indicator data source and adds more complexity.
In this example you start wanting to show the change in the number of open incidents over time. Then you want to show the trend, and then the number of open incidents broken down by priority. Finally you want to compare the number of open incidents against the number of new incidents.
- First you search for Data Visualizations in the Unified Navigation and select New.
- In the empty new data visualization, you select Add data source.
- You want to use the indicator Number of open incidents. Fortunately, this indicator has been used before and is listed under the Suggested data sources, saving you the trouble of searching for it. You can tell that Number of
open incidents is an indicator data source because of the little column-and-trend icon next to it.
- You return to the visualization and see that the Line type has been selected by default. Line is the most common type of time series, and a time series is the usual visualization for an indicator. You also have an open
Configuration panel for this data visualization, next to the line chart. The chart changes in real time as you configure the visualization.
- The data presentation doesn't look so great, because you only created the indicator on January 11. Fortunately, the Configuration panel has a Date range section where you can trim the dates that are shown. In this case, you
select Show maximum range, and it shows all the dates for which there are data, but only those dates.
- You would also like to see what more information you can give about this data, so you expand the Additional settings section. For indicators, these settings are the same as the KPI Details chart options. For more information, seeChart options in KPI Details under the KPI Details documentation. If you have the necessary roles, you can set targets and thresholds for an indicator in KPI Details.
- You decide to show the data trend, to give the viewer an idea of where the indicators were heading before the Christmas break.
- Now you have a new task, which is to duplicate this data visualization but split up the number of incidents into groups according to their priority. You group data on a time series visualization in the Group
by section of the Configuration panel. So you expand that section and discover that there is already a Priority breakdown for the Number of open incidents indicator. You select that breakdown.
- You get a separate line for every Group by value. Here you see that you can no longer show the trend. If you expand the Additional settings section in the Configuration panel again,
you see that no extra information besides the forecast can be shown now that you have set a Group by value.
- Now you have an additional requirement, which is to display the Number of new incidents indicator in the same visualization, for comparison. To show this indicator, you expand the Data section in the
Configuration panel and select + Add data source under Data sources.
- Then you search for the Number of new incidents indicator and add it.The result is a new line in your visualization for the Number of new incidents.
- You find this difficult to read and aren't sure that this is the best visualization to use. After reading Time series visualization type use cases, you decide to change the visualization to a column display.
- This is certainly an improvement, but you think you could do better still.
- Fortunately, you can set different visualization types for different metrics. You go to the Metrics tiles and expand the menu under the visualization type icon for Number of new incidents. Here you choose the Line visualization
again. You can only do this if you have more than one metric.
- You also have the option to set different Y-axes for Number of open incidents and Number of new incidents, through the More options menu on each Metric tile. However, the scales for the two data sources are not different enough
for this to help.
- The visualization is still a little busy, but a viewer can point their cursor to a column and see the breakdown of scores for that date.
- The last thing you do is to make the legends more readable. Right now the entries are truncated before a viewer could see what each priority actually is. So you try expanding the legend item width to 300px.
- That's it! You save the visualization, which is ready for you to add to dashboards. If you have the right roles, you can save the visualization in the Data Visualizations library for other dashboard designers to use.