Repo sync for protected branch

data-explorer/create-cluster-and-database.md

@@ -3,7 +3,7 @@ title: "Quickstart: Create an Azure Data Explorer cluster and database"
 description: In this quickstart, you learn how to create an Azure Data Explorer cluster and database.
 ms.reviewer: mblythe
 ms.topic: quickstart
-ms.date: 06/03/2025
+ms.date: 06/05/2025
 ms.custom: mode-portal
 adobe-target: true
 
@@ -69,7 +69,7 @@ Create an Azure Data Explorer cluster with a defined set of compute and storage
     | Region | *West US* or *West US 2* | Select *West US* or *West US 2* (if using availability zones) for this quickstart. For a production system, select the region that best meets your needs.
     | Workload | *Dev/Test* | Select *Dev/Test* for this quickstart. For a production system, select the specification that best meets your needs.
     | Compute specifications | *Dev(No SLA)_Standard_E2a_v4* | Select *Dev(No SLA)_Standard_E2a_v4* for this quickstart. For a production system, select the specification that best meets your needs.
-    | Availability zones | On | Turning on this feature distributes the cluster storage and compute resources across multiple physical zones within a region for added protection and availability. By default, this feature is turned on if zones are supported in the region. If fewer than 3 zones are available for the compute instances, the portal displays the number of supported zones. Deployment to availability zones is possible when creating the cluster or [can be migrated later](migrate-cluster-to-multiple-availability-zone.md). Read more about [Azure Availability Zones](/azure/availability-zones/az-overview).|
+    | Availability zones | On | Turning on this feature distributes the cluster storage and compute resources across multiple physical zones within a region for added protection and availability. By default, this feature is turned on if zones are supported in the region. If fewer than three zones are available for the compute instances, the portal displays the number of supported zones. Deployment to availability zones is possible when creating the cluster or [can be migrated later](migrate-cluster-to-multiple-availability-zone.md). Read more about [Azure Availability Zones](/azure/availability-zones/az-overview).|
 
 1. Select **Review + create** to review your cluster details, and on the next screen select **Create** to provision the cluster. Provisioning typically takes about 10 minutes.
 
@@ -120,7 +120,7 @@ To create a database in your full cluster:
     |---|---|---|
     | Admin | *Default selected* | The admin field is disabled. New admins can be added after database creation. |
     | Database name | *TestDatabase* | The name of database to create. The name must be unique within the cluster. |
-    | Retention period | *365* | The number of days that data is guaranteed to be kept available for querying. The period is measured from the time data is ingested. |
+    | Retention period | *365* | The number of days that data is available for querying. The period is measured from the time data is ingested. |
     | Cache period | *31* | The number of days to keep frequently queried data available in SSD storage or RAM to optimize querying. |
 
     :::image type="content" source="media/create-cluster-and-database/create-test-database.png" alt-text="Create database form." lightbox="media/create-cluster-and-database/create-test-database.png":::
@@ -170,7 +170,7 @@ You can stop and restart a cluster depending on business needs. Stopping the clu
     :::image type="content" source="media/create-cluster-and-database/stop-button.png" alt-text="Screenshot of the Azure portal and cluster stop button." lightbox="media/create-cluster-and-database/stop-button.png":::
 
     > [!NOTE]
-    > When the cluster is stopped, data is not available for queries, and you can't ingest new data.
+    > When the cluster is stopped, data isn't available for queries, and you can't ingest new data.
 
 1. To restart the cluster, at the top of the **Overview** tab, select **Start**.
 

data-explorer/dashboard-customize-visuals.md

@@ -3,7 +3,7 @@ title: Customize Azure Data Explorer dashboard visuals
 description: Easily customize your Azure Data Explorer dashboard visuals
 ms.reviewer: gabil
 ms.topic: how-to
-ms.date: 01/31/2024
+ms.date: 06/10/2025
 ---
 
 # Customize Azure Data Explorer dashboard visuals
@@ -14,6 +14,9 @@ All visualizations that are created in the context of the [render operator](/kus
 
 ## Prerequisites
 
+Review Visualize data with Azure Data Explorer dashboards.
+
+* Ensure that you have the editor permission on an Azure Data Explorer dashboard.
 * [Visualize data with Azure Data Explorer dashboards](azure-data-explorer-dashboards.md)
 * Editor permissions on an Azure Data Explorer dashboard
 

data-explorer/dashboard-parameters.md

@@ -3,7 +3,7 @@ title: Use parameters in Azure Data Explorer dashboards
 description: Learn how to use parameters as a building block for dashboard filters.
 ms.reviewer: gabil
 ms.topic: how-to
-ms.date: 10/19/2023
+ms.date: 06/05/2025
 ---
 
 # Use parameters in Azure Data Explorer dashboards
@@ -52,12 +52,12 @@ In the **Add parameter** pane, configure the following properties:
 |Field  |Description |
 |---------|---------|
 |**Label**|The name of the parameter shown on the dashboard or the edit card.|
-|**Parameter type**|One of the following parameters:<ul><li>**Single selection**: Only one value can be selected in the filter as input for the parameter.</li><li>**Multiple selection**: One or more values can be selected in the filter as input(s) for the parameter.</li><li>**Time range**: Allows creating additional parameters to filter the queries and dashboards based on time. Every dashboard has a time range picker by default.</li><li>**Free text**: Doesn't have any values populated in the filter. The user can type a value or copy/paste a value to the text field. The filter keeps the recent values used.</li></ul>|
+|**Parameter type**|One of the following parameters:<ul><li>**Single selection**: Only one value can be selected in the filter as input for the parameter.</li><li>**Multiple selection**: One or more values can be selected in the filter as input(s) for the parameter.</li><li>**Time range**: Allows creating more parameters to filter the queries and dashboards based on time. Every dashboard has a time range picker by default.</li><li>**Free text**: Doesn't have any values populated in the filter. The user can type a value or copy/paste a value to the text field. The filter keeps the recent values used.</li></ul>|
 |**Variable name**|The name of the parameter to be used in the query. Tip: Prefixing variable names with a distinctive character, such as an underscore character (_), makes them easier to find when writing queries. |
 |**Data type**|The data type of the parameter values.|
-|**Show on pages**|Select the pages where this parameter will be displayed. The **Select all** option shows the parameter on all pages.|
+|**Show on pages**|Select the pages where this parameter is displayed. The **Select all** option shows the parameter on all pages.|
 |**Source**|The source of the parameter values: <ul><li>**Fixed values**: Manually introduced static filter values. </li><li>**Query**: Dynamically introduced values using a KQL query.</li></ul>|
-|**Default value**|The default value of the filter. The filter will start always with the default value upon initial rendering of the dashboard.|
+|**Default value**|The default value of the filter. The filter always starts with the default value upon initial rendering of the dashboard.|
 |**Add a "Select all" value**|Applicable only to single selection and multiple selection parameter types. Used to retrieve data for all the parameter values. This value should be built into the query to provide the functionality. For more examples of building such queries, see [Use the multiple-selection query-based parameter](#multiple-selection-fixed-values-parameters).|
 
 ## Manage parameters
@@ -365,7 +365,7 @@ To create a cross-filter, you must turn on the option in the visual, and then sp
 
 ## Interact with your data using cross-filter
 
-Once the cross-filter is defined, you can use it to interact with your data. In visuals where you've defined cross-filters, you can select data points and use their values to filter the current dashboard page. For table visuals, select data points by right-clicking on the relevant cell and then in the context menu, select **Cross-filter**.
+Once the cross-filter is defined, you can use it to interact with your data. In visuals where you define cross-filters, you can select data points and use their values to filter the current dashboard page. For table visuals, select data points by right-clicking on the relevant cell and then in the context menu, select **Cross-filter**.
 
 :::image type="content" source="media/dashboard-parameters/cross-filter.jpg" alt-text="Screenshot of a table visual, showing the cross-filter context menu option.":::
 
@@ -379,13 +379,13 @@ With drillthrough, you can select a value in a visual and use it to filter the v
 
 ### Define a drillthrough
 
-To create a drillthrough, you must first turn it on in the visual and then add one or more drillthroughs as required.
+To create a drillthrough, you must first turn on drillthroughs in the visual and then add one or more drillthroughs as required.
 
 1. Edit the visual where you want to add a drillthrough. Make sure that the **Visual** tab is selected.
 
 1. In the right pane, select **Interactions**, then turn on drillthrough.
 
-    :::image type="content" source="media/dashboard-parameters/drillthrough-visual-create.png" alt-text="Screenshot of drillthrough page, showing the turn on option.":::
+    :::image type="content" source="media/dashboard-parameters/drillthrough-visual-create.png" alt-text="Screenshot of drillthrough page, showing the turn-on option.":::
 
 1. Under **Drillthrough**, select **Create new**, and specify the following information. Optionally select **Add another pair** to add multiple parameters for a target page. Repeat this step to add drillthroughs to other pages in the current dashboard using different parameters.
 
@@ -401,11 +401,11 @@ To create a drillthrough, you must first turn it on in the visual and then add o
 
 ## Interact with your data using drillthroughs
 
-Once drillthroughs are defined, you can use them to interact with your data. To do so, in visuals or tables where you've defined a drillthrough, right-click on a data point, and then select **Drill through to** > *destination page*. The values from the data point will be used as the parameters to filter the visuals on the target page.
+Once drillthroughs are defined, you can use them to interact with your data. To do so, in visuals or tables where you define a drillthrough, right-click on a data point, and then select **Drill through to** > *destination page*. The values from the data point are used as the parameters to filter the visuals on the target page.
 
 :::image type="content" source="media/dashboard-parameters/drillthrough-combined.jpg" alt-text="Screenshot of a dashboard visual, showing the drillthrough interaction.":::
 
-To return to the source page, in the top-right of the destination page, select **Reset**. All filters assigned by the drillthrough will be reset.
+To return to the source page, in the top-right of the destination page, select **Reset**. All filters assigned by the drillthrough are reset.
 
 ## Use filter search for single and multiple selection filters
 

data-explorer/data-explorer-overview.md

@@ -3,7 +3,7 @@ title: What is Azure Data Explorer?
 description: Azure Data Explorer is a fast and highly scalable data exploration service for log and telemetry data.
 ms.reviewer: mblythe
 ms.topic: overview
-ms.date: 06/03/2025
+ms.date: 06/10/2025
 adobe-target: true
 
 # Customer intent: As a data analyst, I want to understand Azure Data Explorer, so I can decide if it's suitable for my analytics workloads.
@@ -13,7 +13,7 @@ adobe-target: true
 
 Azure Data Explorer is a fully managed, high-performance, big data analytics platform that makes it easy to analyze high volumes of data in near real time. The Azure Data Explorer toolbox gives you an end-to-end solution for data ingestion, query, visualization, and management.
 
-By analyzing structured, semi-structured, and unstructured data across time series, and by using Machine Learning, Azure Data Explorer makes it simple to extract key insights, spot patterns and trends, and create forecasting models. Azure Data Explorer uses a traditional relational model, organizing data into tables with strongly-typed schemas. Tables are stored within databases, and a cluster can manage multiple databases. Azure Data Explorer is scalable, secure, robust, and enterprise-ready, and is useful for log analytics, time series analytics, IoT, and general-purpose exploratory analytics.
+By analyzing structured, semi-structured, and unstructured data across time series, and by using Machine Learning, Azure Data Explorer makes it simple to extract key insights, spot patterns and trends, and create forecasting models. Azure Data Explorer uses a traditional relational model, organizing data into tables with strongly typed schemas. Tables are stored within databases, and a cluster can manage multiple databases. Azure Data Explorer is scalable, secure, robust, and enterprise-ready, and is useful for log analytics, time series analytics, IoT, and general-purpose exploratory analytics.
 
 Azure Data Explorer capabilities are extended by other services built on its query language: [Kusto Query Language (KQL)](/kusto/query/index?view=azure-data-explorer&preserve-view=true). These services include [Azure Monitor logs](/azure/log-analytics/), [Application Insights](/azure/application-insights/), [Time Series Insights](/azure/time-series-insights/), and [Microsoft Defender for Endpoint](/microsoft-365/security/defender-endpoint/microsoft-defender-endpoint).
 
@@ -68,7 +68,7 @@ Generally speaking, when you interact with Azure Data Explorer, you're going to
 > [!NOTE]
 > You can access your Azure Data Explorer resources either in the [Azure Data Explorer web UI](web-query-data.md) or by using [SDKs](/kusto/api/index?view=azure-data-explorer&preserve-view=true).
 
-1. **Create database:** Create a *cluster* and then create one or more *databases* in that cluster. Each Azure Data Explorer cluster can hold up to 10,000 databases and each database up to 10,000 tables. The data in each table is stored in data shards also called "extents". All data is automatically indexed and partitioned based on the ingestion time. This means you can store a large ammount of varied data and because of the way it's stored, you get fast access to querying it. [Quickstart: Create an Azure Data Explorer cluster and database](create-cluster-and-database.md)
+1. **Create database:** Create a *cluster* and then create one or more *databases* in that cluster. Each Azure Data Explorer cluster can hold up to 10,000 databases and each database up to 10,000 tables. The data in each table is stored in data shards also called "extents". All data is automatically indexed and partitioned based on the ingestion time. This means you can store a large amount of varied data and because of the way it's stored, you get fast access to querying it. [Quickstart: Create an Azure Data Explorer cluster and database](create-cluster-and-database.md)
 
 1. **Ingest data:** Load data into database tables so that you can run queries against it. Azure Data Explorer supports several [ingestion methods](ingest-data-overview.md), each with its own target scenarios. These methods include ingestion tools, connectors and plugins to diverse services, managed pipelines, programmatic ingestion using SDKs, and direct access to ingestion. Get started with the [get data experience](ingest-data-overview.md).