Merge pull request #1574 from HeidiSteen/release-azure-search

Portal wizard data sources

Author: ttorble

articles/search/.openpublishing.redirection.search.json

@@ -1,5 +1,25 @@
 {
     "redirections": [
+        {
+            "source_path_from_root": "/articles/search/cognitive-search-quickstart-blob.md",
+            "redirect_url": "/azure/search/search-get-started-skillset",
+            "redirect_document_id": true
+        },
+        {
+            "source_path_from_root": "/articles/search/search-howto-connecting-azure-sql-database-to-azure-search-using-indexers.md",
+            "redirect_url": "/azure/search/search-how-to-index-sql-database",
+            "redirect_document_id": true
+        },
+        {
+            "source_path_from_root": "/articles/search/search-howto-connecting-azure-sql-mi-to-azure-search-using-indexers.md",
+            "redirect_url": "/azure/search/search-how-to-index-sql-managed-instance",
+            "redirect_document_id": true
+        },
+        {
+            "source_path_from_root": "/articles/search/search-howto-connecting-azure-sql-iaas-to-azure-search-using-indexers.md",
+            "redirect_url": "/azure/search/search-how-to-index-sql-server",
+            "redirect_document_id": true
+        },
         {
             "source_path_from_root": "/articles/search/index-projections-concept-intro.md",
             "redirect_url": "/azure/search/search-how-to-define-index-projections",

articles/search/cognitive-search-skill-image-analysis.md

@@ -23,11 +23,13 @@ This skill uses the machine learning models provided by [Azure AI Vision](/azure
 + The file size of the image must be less than 4 megabytes (MB)
 + The dimensions of the image must be greater than 50 x 50 pixels
 
+Supported data sources for OCR and image analysis are blobs in Azure Blob Storage and Azure Data Lake Storage (ADLS) Gen2, and image content in OneLake. Images can be standalone files or embedded images in a PDF or other files.
+
 This skill is implemented using the [AI Image Analysis API](/azure/ai-services/computer-vision/overview-image-analysis) version 3.2. If your solution requires calling a newer version of that service API (such as version 4.0), consider implementing through [Web API custom skill](cognitive-search-custom-skill-web-api.md).
 
 > [!NOTE]
 > This skill is bound to Azure AI services and requires [a billable resource](cognitive-search-attach-cognitive-services.md) for transactions that exceed 20 documents per indexer per day. Execution of built-in skills is charged at the existing [Azure AI services pay-as-you go price](https://azure.microsoft.com/pricing/details/cognitive-services/).
-> 
+>
 > In addition, image extraction is [billable by Azure AI Search](https://azure.microsoft.com/pricing/details/search/).
 >
 

articles/search/cognitive-search-skill-ocr.md

@@ -22,14 +22,16 @@ An OCR skill uses the machine learning models provided by [Azure AI Vision](/azu
 
 + For Greek and Serbian Cyrillic, the legacy [OCR in version 3.2](https://github.com/Azure/azure-rest-api-specs/tree/master/specification/cognitiveservices/data-plane/ComputerVision/stable/v3.2) API is used.
 
-The **OCR** skill extracts text from image files. Supported file formats include:
+The **OCR** skill extracts text from image files and embedded images. Supported file formats include:
 
 + .JPEG
 + .JPG
 + .PNG
 + .BMP
 + .TIFF
 
+Supported data sources for OCR and image analysis are blobs in Azure Blob Storage and Azure Data Lake Storage (ADLS) Gen2, and image content in OneLake. Images can be standalone files or embedded images in a PDF or other files.
+
 > [!NOTE]
 > This skill is bound to Azure AI services and requires [a billable resource](cognitive-search-attach-cognitive-services.md) for transactions that exceed 20 documents per indexer per day. Execution of built-in skills is charged at the existing [Azure AI services pay-as-you go price](https://azure.microsoft.com/pricing/details/cognitive-services/).
 >

articles/search/media/search-get-started-portal-import-vectors/data-lake-storage.png

@@ -8,7 +8,7 @@ ms.service: azure-ai-search
 ms.custom:
   - build-2024
 ms.topic: quickstart
-ms.date: 11/19/2024
+ms.date: 11/20/2024
 ---
 
 # Quickstart: Vectorize text and images by using the Azure portal
@@ -27,15 +27,15 @@ This quickstart helps you get started with [integrated vectorization](vector-sea
 
 ### Supported data sources
 
-+ [Azure Data Lake Storage (ADLS) Gen2](/azure/storage/blobs/create-data-lake-storage-account) (a storage account with a hierarchical namespace).
+The **Import and vectorize data** wizard [supports a wide range of Azure data sources](search-import-data-portal.md#supported-data-sources-and-scenarios), but this quickstart provides steps for just those data sources that work with whole files:
 
-+ [Azure Storage](/azure/storage/common/storage-account-create) for blobs, files, and tables. Azure Storage must be a standard performance (general-purpose v2) account. Access tiers can be hot, cool, and cold.
++ [Azure Blob Storage](search-howto-indexing-azure-blob-storage.md) for blobs and tables. Azure Storage must be a standard performance (general-purpose v2) account. Access tiers can be hot, cool, and cold.
 
-+ [Azure Cosmos DB](/azure/cosmos-db/nosql/quickstart-portal) for NoSQL, Mongo DB, and Apache Gremlin.
++ [Azure Data Lake Storage (ADLS) Gen2](/azure/storage/blobs/create-data-lake-storage-account) (an Azure Storage account with a hierarchical namespace enabled). You can confirm that you have Data Lake Storage by checking the **Properties** tab on the **Overview** page.
 
-+ [Azure SQL Database](/azure/azure-sql/database/single-database-create-quickstart), [Azure SQL Managed Instance](/azure/azure-sql/managed-instance/instance-create-quickstart), and Azure SQL Server virtual machines.
+   :::image type="content" source="media/search-get-started-portal-import-vectors/data-lake-storage.png" alt-text="Screenshot of the storage account properties page showing Data Lake Storage.":::
 
-+ [OneLake lakehouse](search-how-to-index-onelake-files.md).
++ [OneLake lakehouse (preview)](search-how-to-index-onelake-files.md).
 
 ### Supported embedding models
 
@@ -45,9 +45,9 @@ Use an embedding model on an Azure AI platform in the [same region as Azure AI S
 |---|---|
 | [Azure OpenAI Service](https://aka.ms/oai/access) | text-embedding-ada-002, text-embedding-3-large, or text-embedding-3-small. |
 | [Azure AI Studio model catalog](/azure/ai-studio/what-is-ai-studio) |  Azure, Cohere, and Facebook embedding models. |
-| [Azure AI services multi-service account](/azure/ai-services/multi-service-resource) | [Azure AI Vision multimodal](/azure/ai-services/computer-vision/how-to/image-retrieval) for image and text vectorization. Azure AI Vision multimodal is available in selected regions. [Check the documentation](/azure/ai-services/computer-vision/how-to/image-retrieval?tabs=csharp) for an updated list. **To use this resource, the account must be in an available region and in the same region as Azure AI Search**. |
+| [Azure AI services multi-service account](/azure/ai-services/multi-service-resource) | [Azure AI Vision multimodal](/azure/ai-services/computer-vision/how-to/image-retrieval) for image and text vectorization. Azure AI Vision multimodal is available in selected regions. [Check the documentation](/azure/ai-services/computer-vision/how-to/image-retrieval?tabs=csharp) for an updated list. Depending on how you [attach the multi-service resource](cognitive-search-attach-cognitive-services.md), the account might need to be in the same region as Azure AI Search. |
 
-If using the Azure OpenAI Service, it must have an associated [custom subdomain](/azure/ai-services/cognitive-services-custom-subdomains). If the service was created through the Azure portal, this subdomain is automatically generated as part of your service setup. Ensure that your service includes a custom subdomain before using it with the Azure AI Search integration.
+If you use the Azure OpenAI Service, the endpoint must have an associated [custom subdomain](/azure/ai-services/cognitive-services-custom-subdomains). A custom subdomain is an endpoint that includes a unique name (for example, `https://hereismyuniquename.cognitiveservices.azure.com`). If the service was created through the Azure portal, this subdomain is automatically generated as part of your service setup. Ensure that your service includes a custom subdomain before using it with the Azure AI Search integration.
 
 Azure OpenAI Service resources (with access to embedding models) that were created in AI Studio aren't supported. Only the Azure OpenAI Service resources created in the Azure portal are compatible with the **Azure OpenAI Embedding** skill integration.
 
@@ -57,9 +57,9 @@ For the purposes of this quickstart, all of the preceding resources must have pu
 
 If private endpoints are already present and you can't disable them, the alternative option is to run the respective end-to-end flow from a script or program on a virtual machine. The virtual machine must be on the same virtual network as the private endpoint. [Here's a Python code sample](https://github.com/Azure/azure-search-vector-samples/tree/main/demo-python/code/integrated-vectorization) for integrated vectorization. The same [GitHub repo](https://github.com/Azure/azure-search-vector-samples/tree/main) has samples in other programming languages.
 
-### Role requirements
+### Permissions
 
-We recommend role assignments for search service connections to other resources.
+You can use key authentication and full access connection strings, or Microsoft Entra ID with role assignments. We recommend role assignments for search service connections to other resources.
 
 1. On Azure AI Search, [enable roles](search-security-enable-roles.md).
 
@@ -81,13 +81,9 @@ For more secure connections:
 
 If you're starting with the free service, you're limited to three indexes, data sources, skillsets, and indexers. Basic limits you to 15. Make sure you have room for extra items before you begin. This quickstart creates one of each object.
 
-### Check for semantic ranker
-
-The wizard supports semantic ranking, but only on the Basic tier and higher, and only if semantic ranker is already [enabled on your search service](semantic-how-to-enable-disable.md). If you're using a billable tier, check whether semantic ranker is enabled.
-
 ## Prepare sample data
 
-This section points you to data that works for this quickstart.
+This section points you to the content that works for this quickstart.
 
 ### [Azure Blob Storage](#tab/sample-data-storage)
 
@@ -111,10 +107,6 @@ This section points you to data that works for this quickstart.
 
 1. Sign in to the [Azure portal](https://portal.azure.com/) with your Azure account, and go to your Azure Storage account.
 
-1. You can confirm that you have Data Lake Storage by checking the **Properties** tab on the **Overview** page.
-
-   :::image type="content" source="media/search-get-started-portal-import-vectors/data-lake-storage.png" alt-text="Screenshot of the storage account properties page showing Data Lake Storage.":::
-
 1. On the left pane, under **Data Storage**, select **Containers**.
 
 1. Create a new container and then upload the [health-plan PDF documents](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/health-plan) used for this quickstart.
@@ -231,7 +223,7 @@ The next step is to connect to a data source to use for the search index.
 
 ### [Azure Blob Storage](#tab/connect-data-storage)
 
-1. On the **Set up your data connection** page, select **Azure Blob Storage**.
+1. On **Connect to your data**, select **Azure Blob Storage**.
 
 1. Specify the Azure subscription.
 
@@ -257,7 +249,7 @@ The next step is to connect to a data source to use for the search index.
 
 ### [ADLS Gen2](#tab/connect-data-adlsgen2)
 
-1. On the **Set up your data connection** page, select **Azure Data Lake**.
+1. On **Connect to your data**, select **Azure Data Lake**.
 
 1. Specify the Azure subscription.
 
@@ -281,11 +273,11 @@ The next step is to connect to a data source to use for the search index.
 
 1. Select **Next**.
 
-### [OneLake (preview)](#tab/connect-data-onelake)
+### [OneLake](#tab/connect-data-onelake)
 
 Support for OneLake indexing is in preview. For more information about supported shortcuts and limitations, see ([OneLake indexing](search-how-to-index-onelake-files.md)).
 
-1. On the **Set up your data connection** page, select **OneLake**.
+1. On **Connect to your data**, select **OneLake**.
 
 1. Specify the type of connection:
 
@@ -304,7 +296,7 @@ Support for OneLake indexing is in preview. For more information about supported
 
 In this step, specify the embedding model for vectorizing chunked data.
 
-Chunking is built-in and nonconfigurable. The effective settings are:
+Chunking is built in and nonconfigurable. The effective settings are:
 
 ```json
 "textSplitMode": "pages",
@@ -336,13 +328,15 @@ Chunking is built-in and nonconfigurable. The effective settings are:
 
    + The identity should have a **Cognitive Services OpenAI User** role on the Azure AI multi-services account.
 
-1. Select the checkbox that acknowledges the billing impact of using these resources.
+1. Select the checkbox that acknowledges the billing effects of using these resources.
 
 1. Select **Next**.
 
 ## Vectorize and enrich your images
 
-If your content includes images, you can apply AI in two ways:
+The health plan PDFs don't include images, so you can skip this step.
+
+However, if you work with content that includes images, you can apply AI in two ways:
 
 + Use a supported image embedding model from the catalog, or choose the Azure AI Vision multimodal embeddings API to vectorize images.
 
@@ -358,7 +352,7 @@ Azure AI Search and your Azure AI resource must be in the same region.
 
 1. Optionally, you can crack binary images (for example, scanned document files) and [use OCR](cognitive-search-skill-ocr.md) to recognize text.
 
-1. Select the checkbox that acknowledges the billing impact of using these resources.
+1. Select the checkbox that acknowledges the billing effects of using these resources.
 
 1. Select **Next**.
 
@@ -470,6 +464,7 @@ Search Explorer accepts text strings as input and then vectorizes the text for v
           }
        ]
    }
+   ```
 
 ## Clean up
 

articles/search/media/search-how-to-index-sql-database/database-online.png

@@ -77,7 +77,7 @@ The **Import data** wizard supports the creation of a skillset and [AI-enrichmen
 
 ### Configure the index
 
-The wizard infers a schema for the built-in hotels-sample index. Follow these steps to configure the index:
+The wizard infers a schema for the built-in hotels-sample index. To configure the index, follow these steps:
 
 1. Accept the system-generated values for the **Index name** (_hotels-sample-index_) and **Key** field (_HotelId_).
 
@@ -174,7 +174,7 @@ The following examples assume the JSON view and the 2024-05-01-preview REST API
 
 ### Filter examples
 
-Parking, tags, renovation date, rating and location are filterable.
+Parking, tags, renovation date, rating, and location are filterable.
 
 ```json
 {
@@ -223,7 +223,7 @@ The default syntax is [simple syntax](query-simple-syntax.md), but if you want f
 }
 ```
 
-By default, misspelled query terms like `seatle` for `Seattle` fail to return matches in a typical search. The `queryType=full` parameter invokes the full Lucene query parser, which supports the tilde `~` operand. When these parameters are present, the query performs a fuzzy search for the specified keyword. The query seeks matching results along with results that are similar to but not an exact match to the keyword. 
+By default, misspelled query terms like `seatle` for `Seattle` fail to return matches in a typical search. The `queryType=full` parameter invokes the full Lucene query parser, which supports the tilde `~` operand. When these parameters are present, the query performs a fuzzy search for the specified keyword. The query matches on documents that are similar to but not an exact match to the keyword. 
 
 Take a minute to try a few of these example queries for your index. To learn more about queries, see [Querying in Azure AI Search](search-query-overview.md).
 

articles/search/media/search-how-to-index-sql-database/tsql-query-results.png

@@ -10,7 +10,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: quickstart
-ms.date: 10/15/2024
+ms.date: 11/20/2024
 ---
 
 # Quickstart: Create a skillset in the Azure portal
@@ -84,6 +84,8 @@ If you get *Error detecting index schema from data source*, the indexer that pow
 
 Next, configure AI enrichment to invoke OCR, image analysis, and natural language processing. 
 
+OCR and image analysis are available for blobs in Azure Blob Storage and Azure Data Lake Storage (ADLS) Gen2, and for image content in OneLake. Images can be standalone files or embedded images in a PDF or other files.
+
 1. For this quickstart, we're using the **Free** Azure AI services resource. The sample data consists of 14 files, so the free allotment of 20 transactions on Azure AI services is sufficient for this quickstart. 
 
    :::image type="content" source="media/cognitive-search-quickstart-blob/cog-search-attach.png" alt-text="Screenshot of the Attach Azure AI services tab." border="true":::