Merge pull request #17194 from DCtheGeek/dmc-links-ads

Links: SQL - ads

Author: MikeRayMSFT

docs/azure-data-studio/azure-resource-explorer.md

@@ -16,7 +16,7 @@ ms.date: 09/24/2018
 In this document, you learn how you can explore and manage Azure SQL Server, Azure SQL database, and Azure SQL Managed Instance resources through Azure Resource Explorer in [!INCLUDE [Azure Data Studio](../includes/name-sos-short.md)].
 
 >[!NOTE]
->The Azure Resource Explorer is supported in SQL Server 2019. After that, you can install the extension through [extension manager](extensions.md) or through **File** > **Install Package from VSIX Package**.
+>The Azure Resource Explorer is supported in SQL Server 2019. After that, you can install the extension through [extension manager](./extensions/add-extensions.md) or through **File** > **Install Package from VSIX Package**.
 
 ## Connect to Azure
 

docs/azure-data-studio/deploy-azure-sql-edge.md

@@ -13,7 +13,7 @@ ms.date: 09/22/2020
 
 # Deploy Azure SQL Edge with Azure Data Studio (Preview)
 
-[Azure SQL Edge](https://docs.microsoft.com/azure/azure-sql-edge/overview) is a relational database engine optimized for IoT and Azure IoT Edge deployments. It provides capabilities to create a high-performance data storage and processing layer for IoT applications and solutions. This article shows you how to deploy an Azure SQL Edge instance with Azure Data Studio and the deployment scenarios that are supported with the deployment wizard.  
+[Azure SQL Edge](/azure/azure-sql-edge/overview) is a relational database engine optimized for IoT and Azure IoT Edge deployments. It provides capabilities to create a high-performance data storage and processing layer for IoT applications and solutions. This article shows you how to deploy an Azure SQL Edge instance with Azure Data Studio and the deployment scenarios that are supported with the deployment wizard.  
 
 The following scenarios are supported by the deployment wizard in Azure Data Studio:
 
@@ -71,11 +71,11 @@ Optionally, a dacpac file can be zipped in a folder and deployed to the new Azur
 
 ## Multiple Devices of an Azure IoT Hub
 
-If you have an existing IoT hub and connected devices, Azure SQL Edge can be deployed to the device based on the resource group, IoT hub name, and a [target condition](https://docs.microsoft.com/azure/iot-edge/module-deployment-monitoring#target-condition) to select device(s).
+If you have an existing IoT hub and connected devices, Azure SQL Edge can be deployed to the device based on the resource group, IoT hub name, and a [target condition](/azure/iot-edge/module-deployment-monitoring#target-condition) to select device(s).
 The IP address provided during the deployment wizard is utilized to generate a quick connect link at the bottom of the notebook.
 
 Optionally, a dacpac file can be zipped in a folder and deployed to the new Azure SQL Edge instance as a part of the process.  If a dacpac file is provided, an Azure Blob Storage account is created in the same resource group.
 
 ## Next steps
 
-- [Learn more about Azure SQL Edge](https://docs.microsoft.com/azure/azure-sql-edge/)
+- [Learn more about Azure SQL Edge](/azure/azure-sql-edge/)

docs/azure-data-studio/extensions/azure-arc-extension.md

@@ -13,7 +13,7 @@ ms.date: 09/22/2020
 
 # Azure Arc extension for Azure Data Studio (Preview)
 
-The [Azure Arc extension (preview)](https://aka.ms/azurearcdata-docs) is an extension for creating and managing Azure Arc data services resources.
+The [Azure Arc extension (preview)](/azure/azure-arc/data/) is an extension for creating and managing Azure Arc data services resources.
 
 **Key actions include:**
 - Create a resource
@@ -56,4 +56,4 @@ Once connected, you can view the resources deployed on the data controller. You
 These dashboards will provide additional information about the resource, including option to open in Azure portal.
 
 ## Next steps
-To learn more about Azure Arc data services, [check our documentation.](https://aka.ms/azurearcdata-docs)
+To learn more about Azure Arc data services, [check our documentation.](/azure/azure-arc/data/)

docs/azure-data-studio/extensions/azure-sql-managed-instance-extension.md

@@ -24,7 +24,7 @@ The Azure SQL Managed Instance extension provides a dashboard for working with a
 ## Install
 
 You can install the official release of this extension. Follow the steps
-in the [Azure Data Studio documentation](../extensions.md).
+in the [Azure Data Studio documentation](./add-extensions.md).
 In the **Extensions** pane, search for "Managed Instance", and install it there. After it's installed, you'll get notified automatically about any future extension updates.
 
 With the extension installed, you'll see a **Managed Instance** tab in Azure Data Studio. Here you can find information specific for your managed instance.

docs/azure-data-studio/extensions/data-virtualization-extension.md

@@ -17,7 +17,7 @@ The Data Virtualization extension for Azure Data Studio provides support for the
 
 ## Install the Data Virtualization extension
 
-To install the Data Virtualization extension, visit [Extend the functionality of Azure Data Studio](../extensions.md).
+To install the Data Virtualization extension, visit [Extend the functionality of Azure Data Studio](./add-extensions.md).
 
 ## Changes in release 1.0
 
@@ -140,4 +140,4 @@ A number of improvements that help extenders were added in this release.
 * Improved reliability when using Create External Data wizard, specifically when connection errors occur.
 * Block use of Create External Data wizard if PolyBase isn't enabled or running in the target server.
 * Spelling and naming fixes related to SQL Server 2019 and Create External Data.
-* Removed a large number of errors from the Azure Data Studio debug console.
+* Removed a large number of errors from the Azure Data Studio debug console.

docs/azure-data-studio/extensions/kusto-extension.md

@@ -13,7 +13,7 @@ ms.date: 09/22/2020
 
 # Kusto (KQL) extension for Azure Data Studio (Preview)
 
-The Kusto (KQL) extension for [Azure Data Studio](../what-is.md) enables you to connect and query to [Azure Data Explorer](https://docs.microsoft.com/azure/data-explorer/data-explorer-overview) clusters.
+The Kusto (KQL) extension for [Azure Data Studio](../what-is.md) enables you to connect and query to [Azure Data Explorer](/azure/data-explorer/data-explorer-overview) clusters.
 
 Users can write and run KQL queries and author notebooks with the [Kusto kernel](../notebooks/notebooks-kusto-kernel.md) complete with IntelliSense.
 
@@ -28,7 +28,7 @@ If you don't have an Azure subscription, create a [free Azure account](https://a
 The following prerequisites are also required:
 
 - [Azure Data Studio installed](../download-azure-data-studio.md).
-- [An Azure Data Explorer cluster and database](https://docs.microsoft.com/azure/data-explorer/create-cluster-database-portal).
+- [An Azure Data Explorer cluster and database](/azure/data-explorer/create-cluster-database-portal).
 
 ## Install the Kusto (KQL) extension
 
@@ -99,7 +99,7 @@ StormEvents
 | where EventType == "Waterspout"
 ```
 
-For more information about writing KQL queries, visit [Write queries for Azure Data Explorer](https://docs.microsoft.com/azure/data-explorer/write-queries#overview-of-the-query-language)
+For more information about writing KQL queries, visit [Write queries for Azure Data Explorer](/azure/data-explorer/write-queries#overview-of-the-query-language)
 
 ## View extension settings
 
@@ -119,7 +119,7 @@ The extensions settings look like this:
 
 ## SandDance visualization
 
-The [SandDance extension](https://docs.microsoft.com/sql/azure-data-studio/sanddance-extension) with the Kusto (KQL) extension in Azure Data Studio bring rich interactive visualization together. From the KQL query result set, select the **Visualizer** button to launch [SandDance](https://sanddance.js.org/).
+The [SandDance extension](../sanddance-extension.md) with the Kusto (KQL) extension in Azure Data Studio bring rich interactive visualization together. From the KQL query result set, select the **Visualizer** button to launch [SandDance](https://sanddance.js.org/).
 
 :::image type="content" source="media/kusto-extension/kusto-extension-sanddance-demo.gif" alt-text="SandDance visualization":::
 
@@ -140,6 +140,6 @@ You can file a [bug](https://github.com/microsoft/azuredatastudio/issues/new?ass
 
 - [Create and run a Kusto notebook](../notebooks/notebooks-kusto-kernel.md)
 - [Kqlmagic notebook in Azure Data Studio](../notebooks/notebooks-kqlmagic.md)
-- [SQL to Kusto cheat sheet](https://docs.microsoft.com/azure/data-explorer/kusto/query/sqlcheatsheet)
-- [What is Azure Data Explorer?](https://docs.microsoft.com/azure/data-explorer/data-explorer-overview)
+- [SQL to Kusto cheat sheet](/azure/data-explorer/kusto/query/sqlcheatsheet)
+- [What is Azure Data Explorer?](/azure/data-explorer/data-explorer-overview)
 - [Using SandDance visualizations](https://sanddance.js.org/)

docs/azure-data-studio/extensions/machine-learning-extension-manage-packages.md

@@ -117,5 +117,5 @@ Follow the steps below to uninstall R packages in your database.
 - [Machine Learning extension in Azure Data Studio](machine-learning-extension.md)
 - [Make predictions](machine-learning-extension-predictions.md)
 - [Import or view models](machine-learning-extension-import-view-models.md)
-- [Notebooks in Azure Data Studio](../notebooks-guidance.md)
-- [SQL machine learning documentation](../../machine-learning/index.yml)
+- [Notebooks in Azure Data Studio](../notebooks/notebooks-guidance.md)
+- [SQL machine learning documentation](../../machine-learning/index.yml)

docs/azure-data-studio/extensions/machine-learning-extension-predictions.md

@@ -50,7 +50,7 @@ Azure Data Studio will create a new T-SQL query with the [PREDICT](../../t-sql/q
 - [Machine Learning extension in Azure Data Studio](machine-learning-extension.md)
 - [Manage packages in database](machine-learning-extension-manage-packages.md)
 - [Import or view models](machine-learning-extension-import-view-models.md)
-- [Notebooks in Azure Data Studio](../notebooks-guidance.md)
+- [Notebooks in Azure Data Studio](../notebooks/notebooks-guidance.md)
 - [SQL machine learning documentation](../../machine-learning/index.yml)
 - [Machine Learning Services in Azure SQL Managed Instance](/azure/azure-sql/managed-instance/machine-learning-services-overview)
-- [Machine learning and AI with ONNX in SQL Edge (Preview)](/azure/azure-sql-edge/onnx-overview)
+- [Machine learning and AI with ONNX in SQL Edge (Preview)](/azure/azure-sql-edge/onnx-overview)

docs/azure-data-studio/extensions/machine-learning-extension.md

@@ -19,7 +19,7 @@ The Machine Learning extension for [Azure Data Studio](../what-is.md) enables yo
 
 The following prerequisites need to be installed on the computer you run Azure Data Studio.
 
-- [Python 3](https://www.python.org/downloads/). Once you have installed Python, you need to specify the local path to a Python installation under [Extension Settings](#settings). If you have used a [Python kernel notebook](../notebooks-tutorial-python-kernel.md) in Azure Data Studio, the extension will use the path from the notebook by default.
+- [Python 3](https://www.python.org/downloads/). Once you have installed Python, you need to specify the local path to a Python installation under [Extension Settings](#settings). If you have used a [Python kernel notebook](../notebooks/notebooks-python-kernel.md) in Azure Data Studio, the extension will use the path from the notebook by default.
 
 - [Microsoft ODBC driver 17 for SQL Server](../../connect/odbc/download-odbc-driver-for-sql-server.md) for Windows, macOS, or Linux.
 
@@ -82,7 +82,7 @@ To use the Machine Learning extension as well as the Python package management i
 
 1. Ensure that **Machine Learning: Enable Python** is enabled. This setting is enabled by default.
 
-1. Provide the path to your pre-existing Python installation under **Machine Learning: Python Path**. This can either be the full path to the Python executable or the folder the executable is in. If you have used a [Python kernel notebook](../notebooks-tutorial-python-kernel.md) in Azure Data Studio, the extension will use the path from the notebook by default.
+1. Provide the path to your pre-existing Python installation under **Machine Learning: Python Path**. This can either be the full path to the Python executable or the folder the executable is in. If you have used a [Python kernel notebook](../notebooks/notebooks-python-kernel.md) in Azure Data Studio, the extension will use the path from the notebook by default.
 
 ### Enable R
 
@@ -109,6 +109,6 @@ Follow the links under **Next steps** to see how you can use the Machine Learnin
 - [Manage packages in database](machine-learning-extension-manage-packages.md)
 - [Make predictions](machine-learning-extension-predictions.md)
 - [Import or view models](machine-learning-extension-import-view-models.md)
-- [Notebooks in Azure Data Studio](../notebooks-guidance.md)
+- [Notebooks in Azure Data Studio](../notebooks/notebooks-guidance.md)
 - [SQL machine learning documentation](../../machine-learning/index.yml)
 - [Machine learning and AI with ONNX in SQL Edge (preview)](/azure/azure-sql-edge/onnx-overview)

docs/azure-data-studio/extensions/powershell-extension.md

@@ -59,8 +59,8 @@ If you are running Azure Data Studio on macOS or Linux, you may also need to ins
 PowerShell Core is an Open Source project on [GitHub](https://github.com/powershell/powershell).
 For more information on installing PowerShell Core on macOS or Linux platforms, see the following articles:
 
-- [Installing PowerShell Core on Linux](https://docs.microsoft.com/powershell/scripting/install/installing-powershell-core-on-linux)
-- [Installing PowerShell Core on macOS](https://docs.microsoft.com/powershell/scripting/install/installing-powershell-core-on-macos)
+- [Installing PowerShell Core on Linux](/powershell/scripting/install/installing-powershell-core-on-linux)
+- [Installing PowerShell Core on macOS](/powershell/scripting/install/installing-powershell-core-on-macos)
 
 ## Example Scripts