New files and TOC update.

Author: fbsolo-ms1

articles/machine-learning/how-to-connection.md

@@ -1,5 +1,5 @@
 ---
-title: Use connections (preview)
+title: Create connections to external data sources (preview)
 titleSuffix: Azure Machine Learning
 description: Learn how to use connections to connect to External data sources for training with Azure Machine Learning.
 services: machine-learning
@@ -9,7 +9,7 @@ ms.topic: how-to
 ms.author: ambadal
 author: AmarBadal
 ms.reviewer: franksolomon
-ms.date: 04/11/2023
+ms.date: 04/13/2023
 ms.custom: data4ml
 
 # Customer intent: As an experienced data scientist with Python skills, I have data located in external sources outside of Azure. I need to make that data available to the Azure Machine Learning platform, to train my machine learning models.

articles/machine-learning/how-to-import-data-assets.md

@@ -1,15 +1,15 @@
 ---
-title: Import Data (preview)
+title: Import data (preview)
 titleSuffix: Azure Machine Learning
-description: Learn how to import data from external sources on to Azure Machine Learning platform
+description: Learn how to import data from external sources to the Azure Machine Learning platform.
 services: machine-learning
 ms.service: machine-learning
 ms.subservice: mldata
 ms.topic: how-to
 ms.author: ambadal
 author: AmarBadal
 ms.reviewer: franksolomon
-ms.date: 04/12/2023
+ms.date: 04/13/2023
 ms.custom: data4ml
 ---
 
@@ -43,9 +43,9 @@ To create and work with data assets, you need:
 
 * [Workspace connections created](how-to-connection.md)
 
-## Importing from external database sources / import from external sources to create a mltable data asset
+## Importing from an external database source as a table data asset
 
-> [!NOTE] 
+> [!NOTE]
 > The external databases can have Snowflake, Azure SQL, etc. formats.
 
 The following code samples can import data from external databases. The `connection` that handles the import action determines the external database data source metadata. In this sample, the code imports data from a Snowflake resource. The connection points to a Snowflake source. With a little modification, the connection can point to an Azure SQL database source and an Azure SQL database source. The imported asset `type` from an external database source is `mltable`.
@@ -102,7 +102,7 @@ ml_client.data.import_data(data_import=data_import)
 
 ---
 
-## Import data from external data and file system resources to create a uri_folder data asset
+## Import data from an external file system source as a folder data asset
 
 > [!NOTE]
 > An Amazon S3 data resource can serve as an external file system resource.
@@ -194,4 +194,4 @@ ml_client.data.show_materialization_status(name="<name>")
 
 - [Read data in a job](how-to-read-write-data-v2.md#read-data-in-a-job)
 - [Working with tables in Azure Machine Learning](how-to-mltable.md)
-- [Access data from Azure cloud storage during interactive development](how-to-access-data-interactive.md)
+- [Access data from Azure cloud storage during interactive development](how-to-access-data-interactive.md)

articles/machine-learning/toc.yml

@@ -592,6 +592,14 @@
         - name: Create data assets
           displayName: Create data assets
           href: how-to-create-data-assets.md
+        - name: Import data from external sources
+          items:
+            - name: Create connections to external data sources (preview)
+              displayName: Create connections to external data sources (preview)
+              href: how-to-connection.md
+            - name: Import data (preview)
+              displayName: Import data (preview)
+              href: how-to-import-data-assets.md
         - name: Access and explore your data
           items:
             - name: Access data during interactive development
@@ -600,12 +608,6 @@
             - name: Access data in jobs
               displayName: Access data in jobs
               href: how-to-read-write-data-v2.md
-            - name: Import data
-              displayName: Import data
-              href: how-to-import-data-assets.md
-            - name: Use connections
-              displayName: Use connections
-              href: how-to-connection.md
             - name: Working with Tables (mltable)
               displayName: Working with Tables (mltable)
               href: how-to-mltable.md
@@ -1084,8 +1086,6 @@
               href: how-to-use-pipeline-ui.md
             - name: How to use parallel job in pipeline
               href: how-to-use-parallel-job-in-pipeline.md
-            - name: How to use pipeline component in pipeline
-              href: how-to-use-pipeline-component.md
             # v1
             - name: Create ML pipelines (Python)
               href: ./v1/how-to-create-machine-learning-pipelines.md
@@ -1233,8 +1233,6 @@
           href: reference-yaml-model.md
         - name: Schedule
           href: reference-yaml-schedule.md
-        - name: Pipeline component
-          href: reference-yaml-component-pipeline.md
         - name: Compute
           items:
             - name: Compute cluster (AmlCompute)