Visualize data with Azure Data Explorer dashboards (Preview)

Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data. Azure Data Explorer provides a web application that enables you to run queries and build dashboards. Dashboards are available in the stand-alone web application, the Azure Data Explorer web UI. Azure Data Explorer is also integrated with other dashboard services like Power BI and Grafana.

Azure Data Explorer dashboards provide three main advantages:

  • Natively export queries from the Azure Data Explorer web UI to Azure Data Explorer dashboards.
  • Explore the data in the Azure Data Explorer web UI.
  • Optimized dashboard rendering performance.

The following image depicts an Azure Data Explorer dashboard.

Screenshot showing an Azure Data Explorer web UI dashboard.

Important

Your data is secure. Dashboards and dashboard-related metadata about users is encrypted at rest using Microsoft-managed keys.

Prerequisites

Create a dashboard

You can create a dashboard in the Azure Data Explorer web UI using the following steps. Alternatively, you can create a dashboard by importing a dashboard file.

  1. In the navigation bar, select Dashboards (Preview) and then select New dashboard.

    New dashboard.

  2. Enter a dashboard name and then select Create.

    Create a dashboard.

Add data source

Add a data source for the dashboard.

  1. Select Data sources.

  2. In the Data sources pane, select New data source.

    Data source.

  3. In the Create new data source pane:

    1. Enter a Data source name.
    2. Enter the Cluster URI region and then select Connect.
    3. Select the Database from the drop-down list.
    4. Select Apply.

    Data source pane.

Use Parameters

Parameters significantly improve dashboard rendering performance, and enable you to use filter values as early as possible in the query. Filtering is enabled when the parameter is included in the query associated with your tile(s). For more information about how to set up and use different kinds of parameters, see Use parameters in Azure Data Explorer dashboards.

  1. Select Parameters on the top bar.

  2. Select the + New parameter button in the Parameters pane.

    Select new parameter.

  3. Enter values for all the mandatory fields and select Done. In this example, we're using a query-based parameter that allows you to select one or more states and see events associated with this selection.

    Parameter pane.

Field Description
Parameter type One of the following:
- Single Selection: Only one value can be selected in the filter as input for the parameter.
- Multiple Selection: One or more values can be selected in the filter as input(s) for the parameter.
- Time Range: Allows creating additional parameters to filter the queries and dashboards based on time. Every dashboard has a time range picker by default.
- The parameter type you select will affect the way you write any query that's based on this parameter.
Variable name The name of the parameter to be used in the query.
Data type The data type of the parameter values.
Pin as dashboard filter The option to pin the parameter-based filter to the dashboard.
Source The source of the parameter values:
- Fixed values: Manually introduced static filter values.
- Query: Dynamically introduced values using a KQL query.
Value column Results column to be used as parameter values. Only applicable for query-based parameters.
Label column Results column to be used for parameter labels. Only applicable for query-based parameters.
Add empty "Select all" value Applicable only to single selection and multiple selection parameter types. Used to retrieve data for all the parameter values.
Display name The name of the parameter shown on the dashboard or the edit card.
Default value The default parameter value.

Parameter query

The following is an example of a query using the parameter defined in Use parameters.

Screenshot of query used to generate parameters.

  1. Select the source data from the drop-down bar.

  2. Enter your query and then select Run.

  3. Select Apply changes.

Note

The parameter query is used to generate dynamically introduced values as parameters using a KQL query. It's not the query used for generating the dashboard visual.

For more information about generating parameter queries, see Create a parameter.

Add tile

Add tile uses Kusto Query Language snippets to retrieve data and render visuals. Each tile/query can support a single visual.

  1. Select Add tile from the dashboard canvas or the top menu bar.

    New query.

  2. In the Query pane,

    1. Select the data source from the drop-down menu.

    2. Type the query, and the select Run. For more information about generating queries that use parameters, see Use parameters in your query.

    3. Select + Add visual.

    Execute query.

  3. In the Visual formatting pane, select Visual type to choose the type of visual.

  4. Select Apply changes to pin the visual to the dashboard.

    Add visual to query.

  5. You can resize the visual and then Save changes to save the dashboard.

    save dashboard.

Share dashboards

Use the share menu to grant permissions for an Azure Active Directory (Azure AD) user or Azure AD group to access the dashboard, change a user's permission level, and share the dashboard link.

Important

To access the dashboard, a dashboard viewer needs the following:

  • Dashboard link for access
  • Dashboard permissions
  • Access to the underlying database in the Azure Data Explorer cluster

Manage permissions

  1. Select the Share menu item in the top bar of the dashboard.

  2. Select Manage permissions from the drop-down.

    Share dashboard drop-down.

Grant permissions

To grant permissions to a user in the Dashboard permissions pane:

  1. Write the user's name or email in Add new members box.
  2. In the Permission level, select one of the following values: Can view or Can edit.
  3. Select Add.

Manage dashboard permissions.

Change a user permission level

To change a user permission level in the Dashboard permissions pane:

  1. Either use the search box or scroll the user list to find the user.
  2. Change the Permission level as needed.

To share the dashboard link, do one of the following:

  • Select Share and then select Copy link
  • In the Dashboard permissions window, select Copy link.

Export dashboards

Use the file menu to export a dashboard to a JSON file. Exporting dashboard can be useful in the following scenarios:

  • Version control: You can use the file to restore the dashboard to a previous version.
  • Dashboard template: You can use the file as template for creating new dashboards.
  • Manual editing: You can edit the file to modify the dashboard. The file can be imported back to the dashboard.

To export a dashboard, in the dashboard, select File > Export to file.

Screenshot of dashboard, showing the export to file option.

The file contains the dashboard data in JSON format, an outline of which is shown in the following snippet.

{
  "id": "{GUID}",
  "eTag": "{TAG}",
  "title": "Dashboard title",
  "tiles": [
    {
      "id": "{GUID}",
      "title": "Tile title",
      "query": "{QUERY}",
      "layout": { "x": 0, "y": 7, "width": 6, "height": 5 },
      "pageId": "{GUID}",
      "visualType": "line",
      "dataSourceId": "{GUID}",
      "visualOptions": {
        "xColumn": { "type": "infer" },
        "yColumns": { "type": "infer" },
        "yAxisMinimumValue": { "type": "infer" },
        "yAxisMaximumValue": { "type": "infer" },
        "seriesColumns": { "type": "infer" },
        "hideLegend": false,
        "xColumnTitle": "",
        "yColumnTitle": "",
        "horizontalLine": "",
        "verticalLine": "",
        "xAxisScale": "linear",
        "yAxisScale": "linear",
        "crossFilterDisabled": false,
        "crossFilter": { "dimensionId": "dragX-timeRange", "parameterId": "{GUID}" },
        "multipleYAxes": {
          "base": { "id": "-1", "columns": [], "label": "", "yAxisMinimumValue": null, "yAxisMaximumValue": null, "yAxisScale": "linear", "horizontalLines": [] },
          "additional": []
        },
        "hideTileTitle": false
      },
      "usedParamVariables": [ "{PARAM}" ]
    }
  ],
  "dataSources": [ {} ],
  "$schema": "https://dataexplorer.azure.com/static/d/schema/20/dashboard.json",
  "autoRefresh": { "enabled": true, "defaultInterval": "15m", "minInterval": "5m" },
  "parameters": [ {} ],
  "pages": [ { "name": "Primary", "id": "{GUID}" } ],
  "schema_version": "20"
}

To create new dashboard from a file

You can use a dashboard file to create a new dashboard, as follows:

  1. In the main dashboard page, select New dashboard > Import from file.

    Screenshot of dashboard, showing the import from file option.

  2. Select the file to import.

  3. Enter a dashboard name, and then select Create.

To update or restore an existing dashboard from a file

You can update an existing dashboard, or restore a previous version, as follows:

  1. In the dashboard, select File > Replace with file.

    Screenshot of dashboard, showing the option to replace with file.

  2. Select the file to update the dashboard.

  3. Select Save changes.

Enable auto refresh

  1. Select Edit in dashboard menu to switch to edit mode.

  2. Select Auto refresh.

    Select auto refresh.

  3. Toggle the option so auto refresh is Enabled.

  4. Select values for Minimum time interval and Default refresh rate.

    Enable auto refresh.

  5. Select Apply and then Save the dashboard.

Note

  • Select the smallest minimum time interval to reduce unnecessary load on the cluster.
  • A dashboard viewer:
    • Can change the minimum time intervals for personal use only.
    • Can't select a value which is smaller than the Minimum time interval specified by the editor.

Next Steps