Merge pull request #106012 from HeidiSteen/heidist-master

Standardized next steps and resets

Author: PRMerger14

articles/search/cognitive-search-tutorial-blob-dotnet.md

@@ -925,11 +925,11 @@ Repeat for additional fields: content, languageCode, keyPhrases, and organizatio
 
 ## Reset and rerun
 
-In the early experimental stages of development, the most practical approach for design iterations is to delete the objects from Azure Cognitive Search and allow your code to rebuild them. Resource names are unique. Deleting an object lets you recreate it using the same name.
+In the early experimental stages of development, the most practical approach for design iteration is to delete the objects from Azure Cognitive Search and allow your code to rebuild them. Resource names are unique. Deleting an object lets you recreate it using the same name.
 
-This tutorial took care of checking for existing indexers and indexes and deleting them if they already existed so that you can rerun your code.
+The sample code for this tutorial checks for existing objects and deletes them so that you can rerun your code.
 
-You can also use the portal to delete indexes, indexers, and skillsets.
+You can also use the portal to delete indexes, indexers, data sources, and skillsets.
 
 ## Takeaways
 
@@ -947,7 +947,7 @@ You can find and manage resources in the portal, using the All resources or Reso
 
 ## Next steps
 
-Customize or extend the pipeline with custom skills. Creating a custom skill and adding it to a skillset allows you to onboard text or image analysis that you write yourself.
+Now that you're familiar with all of the objects in an AI enrichment pipeline, let's take a closer look at skillset definitions and individual skills.
 
 > [!div class="nextstepaction"]
-> [Example: Creating a custom skill for AI enrichment](cognitive-search-create-custom-skill-example.md)
+> [How to create a skillset](cognitive-search-defining-skillset.md)

articles/search/cognitive-search-tutorial-blob-python.md

@@ -508,19 +508,13 @@ You can use GET or POST, depending on query string complexity and length. For mo
 
 ## Reset and rerun
 
-In the early stages of development, it's practical to delete objects from Azure Cognitive Search and allow your code to rebuild them. Resource names are unique. Deleting an object lets you recreate it using the same name.
+In the early experimental stages of development, the most practical approach for design iteration is to delete the objects from Azure Cognitive Search and allow your code to rebuild them. Resource names are unique. Deleting an object lets you recreate it using the same name.
 
-To re-index your documents with the new definitions:
-
-1. Delete the indexer, index, and skillset.
-2. Modify objects definitions.
-3. Recreate objects on your service. Recreating the indexer runs the pipeline. 
-
-You can use the portal to delete indexes, indexers, and skillsets. When you delete the indexer, you can optionally, selectively delete the index, skillset, and data source at the same time.
+You can use the portal to delete indexes, indexers, data sources, and skillsets. When you delete the indexer, you can optionally, selectively delete the index, skillset, and data source at the same time.
 
 ![Delete search objects](./media/cognitive-search-tutorial-blob-python/py-delete-indexer-delete-all.png "Delete search objects in the portal")
 
-You can also delete them using a script. The following script will delete the skillset we created. You can easily modify the request to delete the index, indexer, and data source.
+You can also delete them using a script. The following script shows how to delete a skillset. 
 
 ```python
 # delete the skillset
@@ -547,7 +541,7 @@ You can find and manage resources in the portal, using the All resources or Reso
 
 ## Next steps
 
-Customize or extend the pipeline with custom skills. Creating a custom skill and adding it to a skillset allows you to onboard text or image analysis that you write yourself.
+Now that you're familiar with all of the objects in an AI enrichment pipeline, let's take a closer look at skillset definitions and individual skills.
 
 > [!div class="nextstepaction"]
-> [Example: Creating a custom skill for AI enrichment](cognitive-search-create-custom-skill-example.md)
+> [How to create a skillset](cognitive-search-defining-skillset.md)

articles/search/cognitive-search-tutorial-blob.md

@@ -488,15 +488,13 @@ These queries illustrate a few of the ways you can work with query syntax and fi
 
 ## Reset and rerun
 
-In the early stages of development, it's practical to delete objects from Azure Cognitive Search and allow your code to rebuild them. Resource names are unique. Deleting an object lets you recreate it using the same name.
+In the early experimental stages of development, the most practical approach for design iteration is to delete the objects from Azure Cognitive Search and allow your code to rebuild them. Resource names are unique. Deleting an object lets you recreate it using the same name.
 
-To re-index your documents with the new definitions:
+You can use the portal to delete indexes, indexers, data sources, and skillsets. When you delete the indexer, you can optionally, selectively delete the index, skillset, and data source at the same time.
 
-1. Delete the indexer, index, and skillset.
-2. Modify objects definitions.
-3. Recreate objects on your service. Recreating the indexer runs the pipeline. 
+![Delete search objects](./media/cognitive-search-tutorial-blob-python/py-delete-indexer-delete-all.png "Delete search objects in the portal")
 
-You can use the portal to delete indexes, indexers, and skillsets, or use **DELETE** and provide URLs to each object. The following command deletes an indexer.
+Or use **DELETE** and provide URLs to each object. The following command deletes an indexer.
 
 ```http
 DELETE https://[YOUR-SERVICE-NAME].search.windows.net/indexers/cog-search-demo-idxr?api-version=2019-05-06
@@ -520,7 +518,7 @@ You can find and manage resources in the portal, using the All resources or Reso
 
 ## Next steps
 
-Customize or extend the pipeline with custom skills. Creating a custom skill and adding it to a skillset allows you to onboard text or image analysis that you write yourself. 
+Now that you're familiar with all of the objects in an AI enrichment pipeline, let's take a closer look at skillset definitions and individual skills.
 
 > [!div class="nextstepaction"]
-> [Example: Creating a custom skill for AI enrichment](cognitive-search-create-custom-skill-example.md)
+> [How to create a skillset](cognitive-search-defining-skillset.md)

articles/search/search-indexer-tutorial.md

@@ -227,6 +227,14 @@ An indexer object is platform-agnostic, where  configuration, scheduling, and in
   }
   ```
 
+## Reset and rerun
+
+In the early experimental stages of development, the most practical approach for design iteration is to delete the objects from Azure Cognitive Search and allow your code to rebuild them. Resource names are unique. Deleting an object lets you recreate it using the same name.
+
+The sample code for this tutorial checks for existing objects and deletes them so that you can rerun your code.
+
+You can also use the portal to delete indexes, indexers, and data sources.
+
 ## Clean up resources
 
 When you're working in your own subscription, at the end of a project, it's a good idea to remove the resources that you no longer need. Resources left running can cost you money. You can delete resources individually or delete the resource group to delete the entire set of resources.
@@ -235,7 +243,7 @@ You can find and manage resources in the portal, using the All resources or Reso
 
 ## Next steps
 
-In Azure Cognitive Search, indexers are available for multiple Azure data sources. As a next step, explore the indexer for Azure Blob storage.
+Now that you're familiar with the basics of SQL Database indexing, let's take a closer look at indexer configuration.
 
 > [!div class="nextstepaction"]
-> [Indexing Documents in Azure Blob Storage](search-howto-indexing-azure-blob-storage.md)
+> [Configure an Azure SQL database indexer](search-howto-connecting-azure-sql-database-to-azure-search-using-indexers.md)

articles/search/search-semi-structured-data.md

@@ -281,6 +281,18 @@ If you'd like to experiment and try a few more queries yourself, feel free to do
 
 The `$filter` parameter only works with metadata that were marked filterable at the creation of your index.
 
+## Reset and rerun
+
+In the early experimental stages of development, the most practical approach for design iteration is to delete the objects from Azure Cognitive Search and allow your code to rebuild them. Resource names are unique. Deleting an object lets you recreate it using the same name.
+
+You can use the portal to delete indexes, indexers, and data sources. Or use **DELETE** and provide URLs to each object. The following command deletes an indexer.
+
+```http
+DELETE https://[YOUR-SERVICE-NAME].search.windows.net/indexers/clinical-trials-json-indexer?api-version=2019-05-06
+```
+
+Status code 204 is returned on successful deletion.
+
 ## Clean up resources
 
 When you're working in your own subscription, at the end of a project, it's a good idea to remove the resources that you no longer need. Resources left running can cost you money. You can delete resources individually or delete the resource group to delete the entire set of resources.
@@ -289,7 +301,7 @@ You can find and manage resources in the portal, using the All resources or Reso
 
 ## Next steps
 
-There are several approaches and multiple options for indexing JSON blobs. As a next step, review and test the various options to see what works best for your scenario.
+Now that you're familiar with the basics of Azure Blob indexing, let's take a closer look at indexer configuration.
 
 > [!div class="nextstepaction"]
-> [How to index JSON blobs using Azure Cognitive Search Blob indexer](search-howto-index-json-blobs.md)
+> [Configure an Azure Blob storage indexer](search-howto-indexing-azure-blob-storage.md)

articles/search/tutorial-multiple-data-sources.md

@@ -335,6 +335,14 @@ In Azure portal, open the search service **Overview** page, and find the **hotel
 
 Click on the hotel-rooms-sample index in the list. You will see a Search Explorer interface for the index. Enter a query for a term like "Luxury". You should see at least one document in the results, and this document should show a list of room objects in its rooms array.
 
+## Reset and rerun
+
+In the early experimental stages of development, the most practical approach for design iteration is to delete the objects from Azure Cognitive Search and allow your code to rebuild them. Resource names are unique. Deleting an object lets you recreate it using the same name.
+
+The sample code for this tutorial checks for existing objects and deletes them so that you can rerun your code.
+
+You can also use the portal to delete indexes, indexers, and data sources.
+
 ## Clean up resources
 
 When you're working in your own subscription, at the end of a project, it's a good idea to remove the resources that you no longer need. Resources left running can cost you money. You can delete resources individually or delete the resource group to delete the entire set of resources.
@@ -343,7 +351,7 @@ You can find and manage resources in the portal, using the All resources or Reso
 
 ## Next steps
 
-There are several approaches and multiple options for indexing JSON blobs. If your source data includes JSON content, you can review these options to see what works best for your scenario.
+Now that you're familiar with the concept of ingesting data from multiple sources, let's take a closer look at indexer configuration, starting with Cosmos DB.
 
 > [!div class="nextstepaction"]
-> [How to index JSON blobs using Azure Cognitive Search Blob indexer](search-howto-index-json-blobs.md)
+> [Configure an Azure Cosmos DB indexer](search-howto-index-cosmosdb.md)