Explore the samples gallery

The Azure Data Explorer web UI has a samples gallery for you to practice writing Kusto Query Language (KQL) queries and commands. This gallery provides sample data with guided tutorials in a free and publicly accessible help cluster.


A Microsoft account or a Microsoft Entra user identity to sign in to the help cluster. An Azure subscription isn't required.

Get started

The following diagram is a high-level view of the databases available in the samples gallery.

Flow chart showing the Azure Data Explorer divided into sample databases.

Take action on sample data

Get started learning about KQL queries with a dataset from the samples gallery.

  1. Sign in to the Azure Data Explorer web UI using your Microsoft account or Microsoft Entra user identity.

  2. In the Home page, select Explore sample data with KQL.

    Screenshot of the Azure Data Explorer web U I showing the home page.

  3. In the Explore data samples dialog box, select a sample dataset and then select Explore.

    Screenshot of Explore data samples dialog box showing sample database options.

    In the cluster connections pane, the help cluster is displayed with sample databases showing stored functions, external tables, materialized views, and database tables. The database selected in the sample data dialogue box is highlighted.

    Screenshot of Azure Data Explorer U I cluster connection pane showing sample databases and tables in a tree diagram.

    This diagram shows a high level view of the architectural data flow, from raw data through ingestion, processing, and materialized views.

    Flow chart showing a process from raw data ingestion to transformed data and materialized views.

Follow the tutorials

The query editor window, located to the right of the cluster connections pane, provides useful tutorials in the form of commonly used queries along with detailed explanations.

We'll take a look at the Metrics database, labeled as SampleMetrics in the cluster connections pane.

The SampleMetrics dataset consists of the following tables:

  • RawServerMetrics: where raw data is ingested for temporary storage.
  • TransformedServerMetrics: where parsed and processed data is stored.
  • SQLServersLocation: containing reference data of servers' location.


You can navigate to other tutorials from the query editor window. Select Open > Open tutorials and then choose the specific tutorial you want to explore.

Screenshot showing Azure Data Explorer web U I dropdown menu to choose sample tutorials in query window.

Run a query

In the query edit window, place your cursor in a query and select Run at the top of the window, or press Shift + Enter to run a query. Results are displayed in the query results pane, directly below the query editor window.

Before running any query or command, take a moment to read the comments above it. The comments include important information. For example, why certain management commands won't work in the help cluster due to lack of permissions. The query editor provides suggestions and warnings as you write queries. To customize which suggestions and warnings you receive, see Set query recommendations.

Screenshot showing the query editor window with sample tutorials.

Learn management commands

Since certain management commands can't be run in the help cluster, you can create your own free cluster to further explore these commands. Some examples of these commands are described in the following table.

Table Description Command
RawServerMetrics The ingestion batching policy can be configured to reduce the default ingestion latency from 5 minutes to 20 seconds, as described. .alter table RawServerMetrics policy ingestionbatching @'{"MaximumBatchingTimeSpan": "00:00:20", "MaximumNumberOfItems": 500,"MaximumRawDataSizeMB": 1024}'
RawServerMetrics The data retention policy can be configured to 10 days to avoid the duplication of data across raw and transformed tables. If needed, you can keep raw data for longer. For example, if there are any issues with the TransformedServerMetrics table, rather than going back to the source data, you can refer to the data in the RawServerMetrics table. .alter table RawServerMetrics policy retention '{"SoftDeletePeriod": "10.00:00:00", "Recoverability": "Enabled"}'
TransformedServerMetrics The update policy can be applied to transform and parse raw data. .alter table TransformedServerMetrics policy update @'[{"IsEnabled": true, "Source": "RawServerMetrics", "Query": "Transform_RawServerMetrics()", "IsTransactional": true, "PropagateIngestionProperties": false}]'