@@ -34,7 +34,7 @@ In this tutorial, you use **Debug Sessions** to find and fix missing inputs and
 
 + [Sample PDFs (clinical trials)](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/_ARCHIVE/clinical-trials/clinical-trials-pdf-19).
 
-+ [Sample debug-sessions.rest file](https://github.com/Azure-Samples/azure-search-rest-samples/blob/main/Debug-sessions/debug-sessions.rest) used to create the enrichment pipeline.
++ [Sample debug-sessions.rest file](https://github.com/Azure-Samples/azure-search-rest-samples/blob/main/debug-sessions/debug-sessions.rest) used to create the enrichment pipeline.
 
 > [!NOTE]
 > This tutorial also uses [Foundry Tools](https://azure.microsoft.com/services/cognitive-services/) for language detection, entity recognition, and key phrase extraction. Because the workload is so small, Foundry Tools is tapped behind the scenes for free processing for up to 20 transactions. This means that you can complete this exercise without having to create a billable Microsoft Foundry resource.

@@ -40,13 +40,15 @@ This quickstart uses a JSON document that contains metadata for 50 fictitious ho
 
 To prepare the sample data for this quickstart:
 
+1. Download the [sample JSON document](https://github.com/Azure-Samples/azure-search-sample-data/blob/main/hotels/HotelsData_toAzureBlobs.json).
+
 1. Sign in to the [Azure portal](https://portal.azure.com/) and select your Azure Storage account.
 
 1. From the left pane, select **Data storage** > **Containers**.
 
 1. Create a container named **hotels-sample**.
 
-1. Upload the [sample JSON document](https://github.com/Azure-Samples/azure-search-sample-data/blob/main/hotels/HotelsData_toAzureBlobs.json) to the container.
+1. Upload the HotelsData_toAzureBlobs.json file to the container.
 
 ## Start the wizard
 
@@ -105,34 +107,34 @@ To configure the index:
    |-------|------------|
    | `HotelId` | Key, Retrievable, Filterable, Sortable, Searchable |
    | `HotelName`, `Category` | Retrievable, Filterable, Sortable, Searchable |
-   | `Description`, `Description_fr` | Retrievable |
+   | `Description`, `Description_fr` | Retrievable, Searchable |
    | `Tags` | Retrievable, Filterable, Searchable |
-   | `ParkingIncluded`, `IsDeleted`, `LastRenovationDate`, `Rating`, `Location` | Retrievable, Filterable, Sortable |
+   | `ParkingIncluded`, `IsDeleted`, `Location` | Retrievable, Filterable, Facetable |
+   | `LastRenovationDate`, `Rating` | Retrievable, Filterable, Sortable |
    | `Address.StreetAddress`, `Rooms.Description`, `Rooms.Description_fr` | Retrievable, Searchable |
-   | `Address.City`, `Address.StateProvince`, `Address.PostalCode`, `Address.Country`, `Rooms.Type`, `Rooms.BedOptions`, `Rooms.Tags` | Retrievable, Filterable, Facetable, Searchable |
+   | `Address.City`, `Address.StateProvince`, `Address.PostalCode`, `Address.Country` | Retrievable, Filterable, Facetable, Searchable, Sortable|
+   | `Rooms.Type`, `Rooms.BedOptions`, `Rooms.Tags` | Retrievable, Filterable, Facetable, Searchable |
    | `Rooms.BaseRate`, `Rooms.SleepsCount`, `Rooms.SmokingAllowed` | Retrievable, Filterable, Facetable |
 
    :::image type="content" source="../../media/search-get-started-portal/configure-index.gif" alt-text="GIF that shows how to configure attributes for fields in the index." lightbox="../../media/search-get-started-portal/configure-index.gif":::
 
-1. Delete the `AzureSearch_DocumentKey` field.
-
 1. Select **Next**.
 
 At a minimum, the index requires a name and a collection of fields. The wizard scans for unique string fields and marks one as the document key, which uniquely identifies each document in the index.
 
-Each field has a name, data type, and attributes that control how the field is used in the index. You can enable or disable the following attributes:
+Each field has a name, [data type](/rest/api/searchservice/supported-data-types), and attributes that control how the field is used in the index. You can enable or disable the following attributes:
 
 | Attribute | Description | Applicable data types |
 |-----------|-------------|------------------------|
 | Retrievable | Fields returned in a query response. | Strings and integers |
-| Filterable | Fields that accept a filter expression. | Integers |
-| Sortable | Fields that accept an orderby expression. | Integers |
-| Facetable | Fields used in a faceted navigation structure. | Integers |
+| Filterable | Fields that accept a filter expression. | Strings and integers |
+| Sortable | Fields that accept an orderby expression. | Strings and integers |
+| Facetable | Fields used in a faceted navigation structure. | Strings and integers |
 | Searchable | Fields used in full-text search. Strings are searchable, but numeric and Boolean fields are often marked as not searchable. | Strings |
 
-Attributes affect storage in different ways. For example, filterable fields consume extra storage, while retrievable fields don't. For more information, see [Example demonstrating the storage implications of attributes and suggesters](../../search-what-is-an-index.md#example-demonstrating-the-storage-implications-of-attributes-and-suggesters).
+Attributes affect storage in different ways. For example, filterable fields consume extra storage, while retrievable fields don't. For more information about attributes and data types, see [Configure field definitions](/azure/search/search-how-to-create-search-index#configure-field-definitions).
 
-If you want autocomplete or suggested queries, specify language **Analyzers** or **Suggesters**.
+If you want autocomplete or suggested queries, specify **Suggesters**.
 
 ### Skip advanced settings
 

@@ -1,112 +0,0 @@
----
-manager: nitinme
-author: haileytap
-ms.author: haileytapia
-ms.service: azure-ai-search
-ms.topic: include
-ms.date: 09/16/2025
----
-
-> [!IMPORTANT]
-> The **Import data** wizard will eventually be deprecated. Most of its functionality is available in the **Import data (new)** wizard, which we recommend for most search scenarios. For more information, see [Import data wizards in the Azure portal](../../search-import-data-portal.md).
-
-In this quickstart, you use the **Import data** wizard and a built-in sample of fictitious hotel data to create your first search index. The wizard requires no code to create an index, helping you write interesting queries within minutes.
-
-The wizard creates multiple objects on your search service, including a searchable [index](../../search-what-is-an-index.md), an [indexer](../../search-indexer-overview.md), and a data source connection for automated data retrieval. At the end of this quickstart, you review each object.
-
-## Prerequisites
-
-+ An Azure account with an active subscription. [Create an account for free](https://azure.microsoft.com/pricing/purchase-options/azure-account?cid=msft_learn).
-
-+ An Azure AI Search service. [Create a service](../../search-create-service-portal.md) or [find an existing service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices) in your current subscription. You can use a free service for this quickstart.
-
-### Check for network access
-
-For this quickstart, which uses built-in sample data, make sure your search service doesn't have [network access controls](../../service-configure-firewall.md). The Azure portal controller uses a public endpoint to retrieve data and metadata from the Microsoft-hosted data source. For more information, see [Secure connections in the import wizards](../../search-import-data-portal.md#secure-connections).
-
-### Check for space
-
-Many customers start with a free search service, which is limited to three indexes, three indexers, and three data sources. This quickstart creates one of each, so before you begin, make sure you have room for extra objects.
-
-On the **Overview** page, select **Usage** to see how many indexes, indexers, and data sources you currently have.
-
-   :::image type="content" source="../../media/search-get-started-portal/overview-quota-usage.png" alt-text="Screenshot of the Overview page for an Azure AI Search service instance in the Azure portal, showing the number of indexes, indexers, and data sources." lightbox="../../media/search-get-started-portal/overview-quota-usage.png":::
-
-## Start the wizard
-
-To start the wizard for this quickstart:
-
-1. Sign in to the [Azure portal](https://portal.azure.com/) and select your search service.
-
-1. On the **Overview** page, select **Import data**.
-
-   :::image type="content" source="../../media/search-import-data-portal/import-data-button.png" alt-text="Screenshot that shows how to open the Import data wizard in the Azure portal.":::
-
-## Create and load a search index
-
-In this section, you create and load an index in four steps.
-
-### Connect to a data source
-
-The wizard creates a data source connection to sample data that Microsoft hosts on Azure Cosmos DB. The sample data is accessed through a public endpoint, so you don't need an Azure Cosmos DB account or source files for this step.
-
-To connect to the sample data:
-
-1. On the **Connect to your data** page, select the **Data Source** dropdown list, and then select **Samples**.
-
-1. Select **hotels-sample** from the list of built-in samples.
-
-1. Select **Next: Add cognitive skills (Optional)**.
-
-   :::image type="content" source="../../media/search-get-started-portal/import-hotels-sample.png" alt-text="Screenshot that shows how to select the hotels-sample data source in the Import data wizard." lightbox="../../media/search-get-started-portal/import-hotels-sample.png":::
-
-### Skip configuration for skills
-
-The wizard supports skillset creation and [AI enrichment](../../cognitive-search-concept-intro.md) during indexing, which are beyond the scope of this quickstart. Skip this step by selecting **Next: Customize target index**.
-
-> [!TIP]
-> For a similar walkthrough that focuses on AI enrichment, see [Quickstart: Create a skillset in the Azure portal](../../search-get-started-skillset.md).
-
-### Configure the index
-
-Based on the structure and content of the sample hotel data, the wizard infers a schema for your search index.
-
-To configure the index:
-
-1. Accept the system-generated values for the index name (**hotels-sample-index**) and key (**HotelId**).
-
-1. Accept the system-generated values for all field attributes.
-
-1. Select **Next: Create an indexer**.
-
-   :::image type="content" source="../../media/search-get-started-portal/hotels-sample-generated-index.png" alt-text="Screenshot that shows the generated index definition for the hotels-sample data source in the Import data wizard." lightbox="../../media/search-get-started-portal/hotels-sample-generated-index.png":::
-
-At a minimum, the index requires a name and a collection of fields. The wizard scans for unique string fields and marks one as the document key, which uniquely identifies each document in the index.
-
-Each field has a name, data type, and attributes that control how the field is used in the index. You can use the checkboxes to enable or disable the following attributes:
-
-| Attribute | Description | Applicable data types |
-|-----------|-------------|------------------------|
-| Retrievable | Fields returned in a query response. | Strings and integers |
-| Filterable | Fields that accept a filter expression. | Integers |
-| Sortable | Fields that accept an orderby expression. | Integers |
-| Facetable | Fields used in a faceted navigation structure. | Integers |
-| Searchable | Fields used in full-text search. Strings are searchable, but numeric and Boolean fields are often marked as not searchable. | Strings |
-
-Attributes affect storage in different ways. For example, filterable fields consume extra storage, while retrievable fields don't. For more information, see [Example demonstrating the storage implications of attributes and suggesters](../../search-what-is-an-index.md#example-demonstrating-the-storage-implications-of-attributes-and-suggesters).
-
-If you want autocomplete or suggested queries, specify language **Analyzers** or **Suggesters**.
-
-### Configure and run the indexer
-
-The last step is to configure and run the indexer, which automates the process of extracting content from your data source and loading it into your index. This step also creates the data source and index objects on your search service.
-
-To configure and run the indexer:
-
-1. Accept the system-generated value for the indexer name (**hotels-sample-indexer**).
-
-1. Accept the default schedule option to run the indexer once and immediately. The sample data is static, so you can't enable change tracking.
-
-1. Select **Submit** to simultaneously create and run the indexer.
-
-   :::image type="content" source="../../media/search-get-started-portal/hotels-sample-indexer.png" alt-text="Screenshot that shows how to configure the indexer for the hotels-sample data source in the Import data wizard." lightbox="../../media/search-get-started-portal/hotels-sample-indexer.png":::

@@ -54,7 +54,7 @@ It can take several minutes for permissions to take effect.
 
 ## Create an index
 
-A search index provides grounding data for the chat model. We recommend the hotels-sample-index, which can be created in minutes and runs on any search service tier. This index is created using built-in sample data.
+A search index provides grounding data for the chat model. We recommend the hotels-sample-index, which you can create by running the [**Import data (new)**](../../search-import-data-portal.md) wizard and following the instructions to create the index.
 
 1. In the Azure portal, [find your search service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices).
 

@@ -56,17 +56,11 @@ It can take several minutes for permissions to take effect.
 
 ## Create an index
 
-A search index provides grounding data for the chat model. We recommend the **hotels-sample-index**, which you can create in minutes and runs on any search service tier. This index uses built-in sample data.
+A search index provides grounding data for the chat model. We recommend the **hotels-sample-index**.
 
 1. In the Azure portal, [find your search service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices).
 
-1. On the **Overview** home page, select [**Import data**](../../search-get-started-portal.md) to start the wizard.
-
-1. On the **Connect to your data** page, select **Samples** from the dropdown list.
-
-1. Choose the **hotels-sample**.
-
-1. Select **Next** through the remaining pages, accepting the default values.
+1. Follow the instructions in [this quickstart](../../search-import-data-portal.md) to create the index.
 
 1. Once the index is created, select **Search management** > **Indexes** from the left menu to open the index.
 

@@ -55,17 +55,11 @@ It can take several minutes for permissions to take effect.
 
 ## Create an index
 
-A search index provides grounding data for the chat model. We recommend the hotels-sample-index, which can be created in minutes and runs on any search service tier. This index is created using built-in sample data.
+A search index provides grounding data for the chat model. We recommend the **hotels-sample-index**.
 
 1. In the Azure portal, [find your search service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices).
 
-1. On the **Overview** home page, select [**Import data**](../../search-get-started-portal.md) to start the wizard.
-
-1. On the **Connect to your data** page, select **Samples** from the dropdown list.
-
-1. Choose the **hotels-sample**.
-
-1. Select **Next** through the remaining pages, accepting the default values.
+1. Follow the instructions in [this quickstart](../../search-import-data-portal.md) to create the index.
 
 1. Once the index is created, select **Search management** > **Indexes** from the left menu to open the index.
 

@@ -59,17 +59,11 @@ It can take several minutes for permissions to take effect.
 
 ## Update the hotels-sample-index
 
-A search index provides grounding data for the chat model. We recommend the hotels-sample-index, which can be created in minutes and runs on any search service tier. This index is created using built-in sample data.
+A search index provides grounding data for the chat model. We recommend the **hotels-sample-index**.
 
 1. In the Azure portal, [find your search service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices).
 
-1. On the **Overview** home page, select [**Import data**](../../search-get-started-portal.md) to start the wizard.
-
-1. On the **Connect to your data** page, select **Samples** from the dropdown list.
-
-1. Choose the **hotels-sample**.
-
-1. Select **Next** through the remaining pages, accepting the default values.
+1. Follow the instructions in [this quickstart](../../search-import-data-portal.md) to create the index.
 
 1. Once the index is created, select **Search management** > **Indexes** from the left menu to open the index.
 

@@ -62,17 +62,11 @@ It can take several minutes for permissions to take effect.
 
 ## Create an index
 
-A search index provides grounding data for the chat model. We recommend the hotels-sample-index, which can be created in minutes and runs on any search service tier. This index is created using built-in sample data.
+A search index provides grounding data for the chat model. We recommend the **hotels-sample-index**.
 
 1. In the Azure portal, [find your search service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices).
 
-1. On the **Overview** home page, select [**Import data**](../../search-get-started-portal.md) to start the wizard.
-
-1. On the **Connect to your data** page, select **Samples** from the dropdown list.
-
-1. Choose the **hotels-sample**.
-
-1. Select **Next** through the remaining pages, accepting the default values.
+1. Follow the instructions in [this quickstart](../../search-import-data-portal.md) to create the index.
 
 1. Once the index is created, select **Search management** > **Indexes** from the left menu to open the index.
 

@@ -30,7 +30,7 @@ We recommend [Visual Studio Code](https://code.visualstudio.com/download) with a
 
    ```http
    ### List existing indexes by name (verify the connection)
-    GET  {{searchUrl}}/indexes?api-version=2025-11-01-preview&$select=name  HTTP/1.1
+    GET  {{searchUrl}}/indexes?api-version=2025-09-01&$select=name  HTTP/1.1
     Authorization: Bearer {{personalAccessToken}}
    ```
 
@@ -49,7 +49,6 @@ To update an index using the REST API, you must provide the entire schema, plus
    "configurations": [
    {
       "name": "semantic-config",
-      "flightingOptIn": false,
       "rankingOrder": "BoostedRerankerScore",
       "prioritizedFields": {
          "titleField": { "fieldName": "HotelName" },
@@ -61,10 +60,10 @@ To update an index using the REST API, you must provide the entire schema, plus
 }
 ```
 
-1. Formulate a POST request specifying the index name, operation, and full JSON schema. All required elements of the schema must be present. This request includes the full schema for hotels-sample-index plus the semantic configuration.
+1. Formulate a PUT request specifying the index name, operation, and full JSON schema. All required elements of the schema must be present. This request includes the full schema for hotels-sample-index plus the semantic configuration.
 
     ```http
-    POST  {{searchUrl}}/indexes?api-version=2025-11-01-preview  HTTP/1.1
+    PUT {{searchUrl}}/indexes/hotels-sample-index?api-version=2025-09-01  HTTP/1.1
     Content-Type: application/json
     Authorization: Bearer {{personalAccessToken}}
     
@@ -112,7 +111,6 @@ To update an index using the REST API, you must provide the entire schema, plus
         "configurations": [
           {
             "name": "semantic-config",
-            "flightingOptIn": false,
             "rankingOrder": "BoostedRerankerScore",
             "prioritizedFields": {
               "titleField": {
@@ -154,14 +152,14 @@ Required semantic parameters include `query_type` and `semantic_configuration_na
 1. Test the connection with a GET request that returns the hotels-sample-index.
 
     ```http
-    GET  {{searchUrl}}/indexes/hotels-sample-index?api-version=2025-11-01-preview  HTTP/1.1
+    GET {{searchUrl}}/indexes/hotels-sample-index?api-version=2025-09-01  HTTP/1.1
     Authorization: Bearer {{personalAccessToken}}
     ```
 
 1. Send a query that includes the semantic query type and configuration name.
 
    ```http
-    POST {{searchUrl}}/indexes/hotels-sample-index/docs/search?api-version=2025-11-01-preview  HTTP/1.1
+    POST {{searchUrl}}/indexes/hotels-sample-index/docs/search?api-version=2025-09-01  HTTP/1.1
     Content-Type: application/json
     Authorization: Bearer {{personalAccessToken}}
     
@@ -241,7 +239,7 @@ Optionally, you can add captions to extract portions of the text and apply hit h
 1. Add the `captions` parameter and send the request.
 
     ```http
-    POST {{searchUrl}}/indexes/hotels-sample-index/docs/search?api-version=2025-11-01-preview  HTTP/1.1
+    POST {{searchUrl}}/indexes/hotels-sample-index/docs/search?api-version=2025-09-01  HTTP/1.1
     Content-Type: application/json
     Authorization: Bearer {{personalAccessToken}}
     
@@ -284,7 +282,7 @@ To produce a semantic answer, the question and answer must be closely aligned, a
 1. Formulate the request using a search string that asks a question.
 
     ```http
-    POST {{searchUrl}}/indexes/hotels-sample-index/docs/search?api-version=2025-11-01-preview  HTTP/1.1
+    POST {{searchUrl}}/indexes/hotels-sample-index/docs/search?api-version=2025-09-01  HTTP/1.1
     Content-Type: application/json
     Authorization: Bearer {{personalAccessToken}}
     

@@ -185,14 +185,14 @@ Pay close attention to skill outputs (targetNames). Outputs written to the enric
     "cognitiveServices": {
         "@odata.type": "#Microsoft.Azure.Search.CognitiveServicesByKey",
         "description": "A Foundry resource in the same region as Search.",
-        "key": ""
+        "key": "{{cognitive-services-key}}"
     },
     "knowledgeStore": null
 }
 ```
 
 > [!NOTE]
-> Under `"cognitiveServices"`, the key field is unspecified because the indexer can use a Foundry resource in the same region as your search service and process up to 20 transactions daily at no charge. The sample data for this example stays under the 20 transaction limit.
+> The indexer can process up to 20 transactions per day at no charge. The sample data for this example stays under the 20-transaction limit, so if you're using the sample data, you can omit the `cognitiveServices` section.
 
 ## Example Shaper skill
 

@@ -27,13 +27,13 @@ Code samples from the Azure AI Search team demonstrate features and workflows. T
 | Sample | Article | Description |
 |--|--|--|
 | [quickstart](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart) | [Quickstart: Full-text search](search-get-started-text.md) | Create, load, and query a search index using sample data. |
-| [quickstart-ACL](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-ACL) | [Query-time ACL and RBAC enforcement](search-query-access-control-rbac-enforcement.md) | Implement query-time access control using role-based access control (RBAC) and access control lists (ACLs). |
 | [quickstart-agentic-retrieval](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-agentic-retrieval) | [Quickstart: Agentic retrieval](search-get-started-agentic-retrieval.md) | Integrate semantic ranking with LLM-powered query planning and answer generation. |
 | [quickstart-RAG](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-RAG) | [Quickstart: Classic generative search (RAG)](search-get-started-rag.md) | Use grounding data from Azure AI Search with a chat completion model from Azure OpenAI. |
 | [quickstart-semantic-search](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-semantic-search) | [Quickstart: Semantic ranking](search-get-started-semantic.md) | Add semantic ranking to an index schema and run semantic queries. |
 | [quickstart-vectors](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-vectors) | [Quickstart: Vector search](search-get-started-vector.md) | Index and query vector content. |
+| [acl](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/acl) | [Query-time ACL and RBAC enforcement](search-query-access-control-rbac-enforcement.md) | Implement query-time access control using role-based access control (RBAC) and access control lists (ACLs). |
 | [custom-analyzers](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/custom-analyzers) | [Tutorial: Create a custom analyzer for phone numbers](tutorial-create-custom-analyzer.md) | Use an analyzer to preserve patterns and special characters in searchable content. |
-| [debug-sessions](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Debug-sessions) | [Tutorial: Fix a skillset using Debug Sessions](cognitive-search-tutorial-debug-sessions.md) | Create search objects that you later debug in the Azure portal. |
+| [debug-sessions](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/debug-sessions) | [Tutorial: Fix a skillset using Debug Sessions](cognitive-search-tutorial-debug-sessions.md) | Create search objects that you later debug in the Azure portal. |
 | [index-json-blobs](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/index-json-blobs) | [Tutorial: Index JSON blobs from Azure Storage](search-semi-structured-data.md) | Create an indexer, data source, and index for nested JSON within a JSON array. Demonstrates the jsonArray parsing model and documentRoot parameters. |
 | [knowledge-store](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/knowledge-store) | [Create a knowledge store using REST](knowledge-store-create-rest.md) | Populate a knowledge store for knowledge mining workflows. |
 | [projections](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/projections) | [Define projections in a knowledge store](knowledge-store-projections-examples.md) | Specify the physical data structures in a knowledge store. |

@@ -9,7 +9,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
   - ignite-2024
-ms.topic: conceptual
+ms.topic: article
 ms.date: 11/19/2025
 ms.update-cycle: 180-days
 ---
@@ -218,7 +218,7 @@ We recommend estimating on a billable tier, Basic or higher. The Free tier runs
 
 1. [Build an initial index](search-what-is-an-index.md) to determine how source data translates to an index. This is the only way to estimate index size. Attributes on the field definitions affect physical storage requirements:
 
-   + For keyword search, marking fields as filterable and sortable [increases index size](search-what-is-an-index.md#example-demonstrating-the-storage-implications-of-attributes-and-suggesters).
+   + For keyword search, marking fields as filterable and sortable [increases index size](search-what-is-an-index.md#physical-structure-and-size).
 
    + For vector search, you can [set parameters to reduce vector size](vector-search-how-to-configure-compression-storage.md).
 

@@ -7,7 +7,7 @@ author: haileytap
 ms.author: haileytapia
 ms.service: azure-ai-search
 ms.topic: quickstart
-ms.date: 09/17/2025
+ms.date: 12/05/2025
 ms.update-cycle: 180-days
 ms.custom:
   - mode-ui
@@ -28,7 +28,7 @@ A demo app can help you visualize how an index functions in a client app, but it
 
 + A [search index](search-what-is-an-index.md) to use as the basis of your generated application.
 
-  This quickstart uses the hotels-sample index. To create the index, run the [**Import data**](search-import-data-portal.md) wizard, select the built-in sample data, and step through the wizard using all the default values.
+  This quickstart uses the hotels-sample index. Follow the instructions in [this quickstart](search-import-data-portal.md) to create the index.
 
   :::image type="content" source="media/search-create-app-portal/import-data-hotels.png" alt-text="Screenshot of the data source page for sample data.":::
 

@@ -149,7 +149,7 @@ Document-level permissions in Azure AI Search provide a structured framework for
 Take a closer look at document-level access control in Azure AI Search with more articles and samples.
 
 - [Tutorial: Index ADLS Gen2 permissions metadata using an indexer](tutorial-adls-gen2-indexer-acls.md)
-- [azure-search-rest-samples/Quickstart-ACL](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-ACL)
+- [azure-search-rest-samples/acl](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/acl)
 - [azure-search-python-samples/Quickstart-Document-Permissions-Push-API](https://github.com/Azure-Samples/azure-search-python-samples/blob/main/Quickstart-Document-Permissions-Push-API)
 - [azure-search-python-samples/Quickstart-Document-Permissions-Pull-API](https://github.com/Azure-Samples/azure-search-python-samples/blob/main/Quickstart-Document-Permissions-Pull-API)
 - [Demo app: Ingesting and honoring sensitivity labels](https://aka.ms/Ignite25/aisearch-purview-sensitivity-labels-repo)

@@ -7,7 +7,7 @@ author: haileytap
 ms.author: haileytapia
 ms.service: azure-ai-search
 ms.topic: quickstart
-ms.date: 09/17/2025
+ms.date: 12/04/2025
 ms.custom:
   - mode-ui
 ---
@@ -24,9 +24,7 @@ This quickstart uses an existing index to demonstrate Search explorer.
 
 + An Azure AI Search service. [Create a service](search-create-service-portal.md) or [find an existing service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices) in your current subscription. For this quickstart, you can use a free service.
 
-+ This quickstart uses the realestate-us-sample index. To create the index, run the [**Import data wizard**](search-import-data-portal.md), select the built-in sample data, and step through the wizard using all the default values.
-
-  :::image type="content" source="media/search-explorer/search-explorer-sample-data.png" alt-text="Screenshot of the sample data sets available in the Import data wizard." border="true" lightbox="media/search-explorer/search-explorer-sample-data.png":::
++ This quickstart uses the hotels-sample index. Follow the instructions in [this quickstart](search-import-data-portal.md) to create the index.
 
 ## Start Search explorer
 
@@ -40,13 +38,11 @@ This quickstart uses an existing index to demonstrate Search explorer.
 
    Alternatively, select the **Search explorer** tab on the index page.
 
-   :::image type="content" source="media/search-explorer/search-explorer-tab.png" alt-text="Screenshot of the Search explorer tab." border="true" lightbox="media/search-explorer/search-explorer-tab.png":::
-
 ## Query three ways
 
 There are three approaches to querying in Search explorer:
 
-+ Query view provides a default search bar. It accepts an empty query or free-text query with Booleans, such as `seattle condo + parking`.
++ Query view provides a default search bar. It accepts an empty query or free-text query with Booleans, such as `ocean view + parking`.
 
 + Image view provides a window to browse or drag and drop PNG, JPG, or JPEG files. Unless your index has an [image vectorizer and an equivalent skill](vector-search-how-to-configure-vectorizer.md#supported-embedding-models), this view is unavailable.
 
@@ -58,9 +54,9 @@ There are three approaches to querying in Search explorer:
 
 Search explorer accepts images as query inputs through **Image view**, which requires that you use a supported vectorizer–skill pair. For more information, see [Configure a vectorizer in a search index](vector-search-how-to-configure-vectorizer.md).
 
-The realestate-us-sample index isn't configured for image vectorization. If you want to run image queries, create an index as described in [Quickstart: Vector search in the Azure portal](search-get-started-portal-import-vectors.md). The quickstart relies on text-based sample data, so you must use documents that contain images.
+The hotels-sample index isn't configured for image vectorization. If you want to run image queries, create an index as described in [Quickstart: Vector search in the Azure portal](search-get-started-portal-import-vectors.md). The quickstart relies on text-based sample data, so you must use documents that contain images.
 
-To run an image query, select or drag an image to the search area, and then select **Search**. Search explorer vectorizes the image and sends the vector to the search engine for query execution. The search engine returns documents that are sufficiently similar to the input image, up to the specified `k` number of results. <!-- This is enabled by [vector search](vector-search-overview.md), which matches documents based on the similarity of their vector representations. -->
+To run an image query, select or drag an image to the search area, and then select **Search**. Search explorer vectorizes the image and sends the vector to the search engine for query execution. The search engine returns documents that are sufficiently similar to the input image, up to the specified `k` number of results.
 
 :::image type="content" source="media/search-get-started-portal-images/image-search.png" alt-text="Screenshot of search results for image search." border="true" lightbox="media/search-get-started-portal-images/image-search.png":::
 
@@ -79,6 +75,8 @@ In Search explorer, POST requests are formulated internally using [Documents - S
 
 For a first look at content, execute an empty search by selecting **Search** with no terms provided. An empty search is useful as a first query because it returns entire documents so that you can review document composition. On an empty search, there's no search score, and documents are returned in arbitrary order (`"@search.score": 1` for all documents). By default, 50 documents are returned per search request.
 
+Add `"count": true` to get the number of matches found in an index. On an empty search, the count is the total number of documents in the index. On a qualified search, it's the number of documents matching the query input. Recall that the service returns the top-50 matches by default, so the count might indicate more matches in the index than what's returned in the results.
+
 Equivalent syntax for an empty search is `*` or `"search": "*"`.
 
    ```json
@@ -90,7 +88,7 @@ Equivalent syntax for an empty search is `*` or `"search": "*"`.
 
    **Results**
 
-   :::image type="content" source="media/search-explorer/search-explorer-example-empty.png" alt-text="Screenshot of unqualified or empty query example." border="true" lightbox="media/search-explorer/search-explorer-example-empty.png":::
+   :::image type="content" source="media/search-explorer/search-explorer-example-count.png" alt-text="Screenshot of a count example." border="true" lightbox="media/search-explorer/search-explorer-example-count.png":::
 
 ### Run a free-text query
 
@@ -102,7 +100,7 @@ Notice that when you provide search criteria, such as query terms or expressions
 
    ```json
    {
-       "search": "Seattle townhouse `Lake Washington` miele OR thermador appliance"
+       "search": "activities `outdoor pool` restaurant OR continental breakfast"
    }
    ```
 
@@ -112,30 +110,15 @@ Notice that when you provide search criteria, such as query terms or expressions
 
    :::image type="content" source="media/search-explorer/search-explorer-example-freetext.png" alt-text="Screenshot of a free text query example." border="true" lightbox="media/search-explorer/search-explorer-example-freetext.png":::
 
-### Count matching documents
-
-Add `"count": true` to get the number of matches found in an index. On an empty search, the count is the total number of documents in the index. On a qualified search, it's the number of documents matching the query input. Recall that the service returns the top-50 matches by default, so the count might indicate more matches in the index than what's returned in the results.
-
-   ```json
-   {
-       "search": "Seattle townhouse `Lake Washington` miele OR thermador appliance",
-       "count": true
-   }
-   ```
-
-   **Results**
-
-   :::image type="content" source="media/search-explorer/search-explorer-example-count.png" alt-text="Screenshot of a count example." border="true" lightbox="media/search-explorer/search-explorer-example-count.png":::
-
 ### Limit fields in search results
 
 Add [`"select"`](search-query-odata-select.md) to limit results to the explicitly named fields for more readable output in **Search explorer**. Only fields attributed as retrievable in the index can show up in results.
 
    ```json
    {
-      "search": "seattle condo",
+      "search": "activities `outdoor pool` restaurant OR continental breakfast",
       "count": true,
-      "select": "listingId, beds, baths, description, street, city, price"
+      "select": "HotelId, HotelName, Tags, Description"
    }
    ```
 
@@ -145,17 +128,17 @@ Add [`"select"`](search-query-odata-select.md) to limit results to the explicitl
 
 ### Return next batch of results
 
-Azure AI Search returns the top-50 matches based on the search rank. To get the next set of matching documents, append `"top": 100` and `"skip": 50` to increase the result set to 100 documents (default is 50, maximum is 1000), skipping the first 50 documents. You can check the document key (`listingID`) to identify a document.
+Azure AI Search returns the top-50 matches based on the search rank. The hotels-sample index only has 50 hotels, so we use a smaller number to illustrate paging. To get the next set of matching documents, append `"top": 20` and `"skip": 10` to increase the result set to 20 documents (default is 50, maximum is 1000), skipping the first 10 documents. You can check the document key (`HotelId`) to identify a document.
 
 Recall that you need to provide search criteria, such as a query term or expression, to get ranked results. Search scores decrease the deeper you reach into search results.
 
    ```json
    {
-      "search": "seattle condo",
+      "search": "activities `outdoor pool` restaurant OR continental breakfast",
       "count": true,
-      "select": "listingId, beds, baths, description, street, city, price",
-      "top": 100,
-      "skip": 50
+      "select": "HotelId, HotelName, Tags, Description",
+      "top": 20,
+      "skip": 10
    }
    ```
 
@@ -165,14 +148,14 @@ Recall that you need to provide search criteria, such as a query term or express
 
 ### Filter expressions (greater than, less than, equal to)
 
-Use the [`filter`](search-query-odata-filter.md) parameter to specify inclusion or exclusion criteria. The field must be attributed as filterable in the index. This example searches for bedrooms greater than three:
+Use the [`filter`](search-query-odata-filter.md) parameter to specify inclusion or exclusion criteria. The field must be attributed as filterable in the index. This example searches for ratings greater than four:
 
    ```json
    {
-       "search": "seattle condo",
+       "search": "activities `outdoor pool` restaurant OR continental breakfast",
        "count": true,
-       "select": "listingId, beds, baths, description",
-       "filter": "beds gt 3"
+       "select": "HotelId, HotelName, Tags, Description, Rating",
+       "filter": "Rating gt 4"
    }
    ```
    
@@ -186,11 +169,11 @@ Add [`orderby`](search-query-odata-orderby.md) to sort results by another field
 
    ```json
    {
-       "search": "seattle condo",
+       "search": "activities `outdoor pool` restaurant OR continental breakfast",
        "count": true,
-       "select": "listingId, price, beds, baths, description",
-       "filter": "beds gt 3",
-       "orderby": "price asc"
+       "select": "HotelId, HotelName, Tags, Description, Rating, LastRenovationDate",
+       "filter": "Rating gt 4",
+       "orderby": "LastRenovationDate desc"
    }
    ```
 
@@ -206,7 +189,7 @@ In this quickstart, you used **Search explorer** to query an index using the RES
 
 + Search results are composed of all fields attributed as retrievable in the index. Select the **Fields** tab to review attributes.
 
-+ Keyword search, similar to what you might enter in a commercial web browser, is useful for testing an end-user experience. For example, assuming the built-in realestate-us-sample index, you can enter `"Seattle apartments lake washington"`, and then you can use Ctrl-F to find terms within the search results.
++ Keyword search, similar to what you might enter in a commercial web browser, is useful for testing an end-user experience. For example, assuming the hotels-sample index, you can enter `"activities 'outdoor pool' restaurant OR continental breakfast"`, and then you can use Ctrl-F to find terms within the search results.
 
 + Query and filter expressions are articulated in a syntax implemented by Azure AI Search. The default is a [simple syntax](/rest/api/searchservice/simple-query-syntax-in-azure-search), but you can optionally use [full Lucene](/rest/api/searchservice/lucene-query-syntax-in-azure-search) for more powerful queries. [Filter expressions](/rest/api/searchservice/odata-expression-syntax-for-azure-search) are articulated in an OData syntax.
 

@@ -7,23 +7,27 @@ author: haileytap
 ms.author: haileytapia
 ms.service: azure-ai-search
 ms.topic: quickstart
-ms.date: 09/16/2025
+ms.date: 12/05/2025
 ms.custom:
   - mode-ui
   - ignite-2023
   - ignite-2024
-zone_pivot_groups: azure-portal-wizards
 ---
 
 # Quickstart: Create a search index in the Azure portal
 
-::: zone pivot="import-data-new"
+[!INCLUDE [Import data (new) instructions](includes/quickstarts/search-get-started-portal-new-wizard.md)]
+
+<!-- Removed this from metadata. Remove the the zone pivot entry on next PR
+zone_pivot_groups: azure-portal-wizards -->
+
+<!-- ::: zone pivot="import-data-new"
 [!INCLUDE [Import data (new) instructions](includes/quickstarts/search-get-started-portal-new-wizard.md)]
 ::: zone-end
 
 ::: zone pivot="import-data"
 [!INCLUDE [Import data instructions](includes/quickstarts/search-get-started-portal-old-wizard.md)]
-::: zone-end
+::: zone-end -->
 
 ## Monitor indexer progress
 
@@ -63,7 +67,7 @@ Review the index definition options to understand what you can and can't edit du
 
 ## Query with Search explorer
 
-You now have a search index that can be queried using [**Search explorer**](search-explorer.md), which sends REST calls that conform to [Documents - Search Post (REST API)](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-05-01-preview&preserve-view=true). This tool supports [simple query syntax](/rest/api/searchservice/simple-query-syntax-in-azure-search) and [full Lucene query syntax](/rest/api/searchservice/lucene-query-syntax-in-azure-search).
+You now have a search index that can be queried using [**Search explorer**](search-explorer.md), which sends REST calls that conform to [Documents - Search Post (REST API)](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2025-11-01-preview&preserve-view=true). This tool supports [simple query syntax](/rest/api/searchservice/simple-query-syntax-in-azure-search) and [full Lucene query syntax](/rest/api/searchservice/lucene-query-syntax-in-azure-search) for keyword search.
 
 To query your search index:
 
@@ -81,7 +85,7 @@ To query your search index:
 
 ## Example queries for hotels-sample index
 
-The following examples assume the JSON view and 2024-05-01-preview REST API version.
+The following examples assume the JSON view and the latest preview REST API version.
 
 > [!TIP]
 > The JSON view supports intellisense for parameter name completion. Place your cursor inside the JSON view and enter a space character to see a list of all query parameters. You can also enter a letter, like `s`, to see only the query parameters that begin with that letter.
@@ -154,7 +158,7 @@ In the Azure portal, you can find and manage resources by selecting **All resour
 
 ## Next step
 
-Try an Azure portal wizard to generate a ready-to-use web app that runs in a browser. Use this wizard on the small index you created in this quickstart, or use one of the built-in sample datasets for a richer search experience.
+Try an Azure portal wizard to generate a ready-to-use web app that runs in a browser. Use this wizard on the small index you created in this quickstart, or use [sample data](https://github.com/Azure-Samples/azure-search-sample-data) for a richer search experience.
 
 > [!div class="nextstepaction"]
 > [Quickstart: Create a demo search app in the Azure portal](search-create-app-portal.md)

@@ -152,7 +152,7 @@ A design pattern for implementing optimistic concurrency should include a loop t
 
 This code snippet illustrates the addition of a synonymMap to an index that already exists.
 
-The snippet gets the hotels-sample-index index, checks the object version on an update operation, throws an exception if the condition fails, and then retries the operation (up to three times), starting with index retrieval from the server to get the latest version.
+The snippet gets the [hotels-sample-index](search-get-started-portal.md), checks the object version on an update operation, throws an exception if the condition fails, and then retries the operation (up to three times), starting with index retrieval from the server to get the latest version.
 
 ```csharp
 private static void EnableSynonymsInHotelsIndexSafely(SearchIndexClient indexClient)

@@ -5,7 +5,7 @@ description: Learn about the Azure portal wizards that create and load an index
 author: HeidiSteen
 ms.author: heidist
 manager: nitinme
-ms.date: 09/16/2025
+ms.date: 12/05/2025
 ms.service: azure-ai-search
 ms.topic: concept-article
 ms.custom:
@@ -39,13 +39,15 @@ Despite their differences, the wizards follow similar workflows for content inge
 | Index creation | ✅ | ✅ |
 | Indexer pipeline creation | ✅ | ✅ |
 | Azure Logic Apps connectors | ❌ | ✅ |
-| Sample data | ✅ | ❌ |
+| Built-in sample data | ❌ | ❌ |
 | Skills-based enrichment | ✅ | ✅ |
 | Vector and multimodal support | ❌ | ✅ |
 | Semantic ranking support | ❌ | ✅ |
 | Knowledge store support | ✅ | ❌ |
 
-This article explains how the wizards work to help you with proof-of-concept testing. For step-by-step instructions using sample data, see [Try the wizards](#try-the-wizards).
+Built-in sample data for the hotels sample index is no longer provided, but you can create an identical index by following the [Quickstart: Create an index for keyword search](search-get-started-portal.md).
+
+This article explains how the wizards work to help you with proof-of-concept testing. For step-by-step instructions, see [Try the wizards](#try-the-wizards).
 
 ## Supported data sources and scenarios
 
@@ -78,15 +80,6 @@ The wizards support the following data sources, most of which use [built-in inde
 
 <sup>2</sup> Instead of using a Logic Apps connector, you can use the Search Service REST APIs to programmatically index data from [Azure File Storage](search-file-storage-integration.md) or [SharePoint](search-how-to-index-sharepoint-online.md).
 
-### Sample data
-
-Microsoft hosts the following sample data so that you can skip the wizard step for data source configuration.
-
-| Sample data | Import data wizard | Import data (new) wizard |
-|--|--|--|
-| Hotels      | ✅ | ❌ |
-| Real estate | ✅ | ❌ |
-
 ### Skills
 
 Each wizard generates a skillset and outputs field mappings based on options you select. After the skillset is created, you can modify its JSON definition to add or remove skills.
@@ -182,10 +175,6 @@ The wizards use the Azure portal controller and public endpoints to make outboun
 
 You can use the wizards over restricted public connections, but not all functionality is available.
 
-+ On a search service, importing the built-in sample data requires a public endpoint and no firewall rules.
-
-  Microsoft hosts the sample data on specific Azure resources. The Azure portal controller connects to these resources over a public endpoint. If your search service is behind a firewall, you get the following error when you attempt to retrieve the sample data: `Import configuration failed, error creating Data Source`, followed by `"An error has occured."`.
-
 + On supported Azure data sources protected by firewalls, you can retrieve data if you have the right firewall rules in place.
 
   The Azure resource must admit network requests from the IP address of the device used on the connection. You should also list Azure AI Search as a trusted service on the resource's network configuration. For example, in Azure Storage, you can list `Microsoft.Search/searchServices` as a trusted service.
@@ -228,10 +217,6 @@ To start the wizards:
 
     The wizards open fully expanded in the browser window, giving you more room to work.
 
-1. If you selected **Import data**, you can select **Samples** to index a Microsoft-hosted dataset from a supported data source.
-
-    :::image type="content" source="media/search-what-is-an-index/add-index-import-samples.png" alt-text="Screenshot of the import data page with the samples option selected." border="true":::
-
 1. Follow the remaining steps to create the index, indexer, and other applicable objects.
 
 You can also launch **Import data** from other Azure services, including Azure Cosmos DB, Azure SQL Database, SQL Managed Instance, and Azure Blob Storage. Look for **Add Azure AI Search** in the left pane on the service overview page.

@@ -44,7 +44,7 @@ Results are mostly tabular, composed of fields of either all `retrievable` field
 
 You can choose which fields are in search results. While a search document might have a large number of fields, typically only a few are needed to represent each document in results. On a query request, append `select=<field list>` to specify which `retrievable` fields should appear in the response.
 
-Pick fields that offer contrast and differentiation among documents, providing sufficient information to invite a clickthrough response on the part of the user. On an e-commerce site, it might be a product name, description, brand, color, size, price, and rating. For the built-in hotels-sample index, it might be the "select" fields in the following example:
+Pick fields that offer contrast and differentiation among documents, providing sufficient information to invite a clickthrough response on the part of the user. On an e-commerce site, it might be a product name, description, brand, color, size, price, and rating. For the [hotels-sample index](search-get-started-portal.md), it might be the "select" fields in the following example:
 
 ```http
 POST /indexes/hotels-sample-index/docs/search?api-version=2025-09-01 
@@ -85,7 +85,7 @@ Azure AI Search uses server-side paging to prevent queries from retrieving too m
 The default page size is 50, while the maximum page size is 1,000. If you specify a value greater than 1,000 and there are more than 1,000 results found in your index, only the first 1,000 results are returned. If the number of matches exceed the page size, the response includes information to retrieve the next page of results. For example:
 
 ```json
-"@odata.nextLink": "https://contoso-search-eastus.search.windows.net/indexes/realestate-us-sample-index/docs/search?api-version=2025-09-01"
+"@odata.nextLink": "https://contoso-search-eastus.search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-09-01"
 ```
 
 The top matches are determined by search score, assuming the query is full text search or semantic. Otherwise, the top matches are an arbitrary order for exact match queries (where uniform `@search.score=1.0` indicates arbitrary ranking).
@@ -95,10 +95,10 @@ Set `top` to override the default of 50. In newer preview APIs, if you're using
 To control the paging of all documents returned in a result set, use `top` and `skip` together. This query returns the first set of 15 matching documents plus a count of total matches.
 
 ```http
-POST https://contoso-search-eastus.search.windows.net/indexes/realestate-us-sample-index/docs/search?api-version=2025-09-01
+POST https://contoso-search-eastus.search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 
 {
-    "search": "condos with a view",
+    "search": "room with a view",
     "count": true,
     "top": 15,
     "skip": 0
@@ -108,10 +108,10 @@ POST https://contoso-search-eastus.search.windows.net/indexes/realestate-us-samp
 This query returns the second set, skipping the first 15 to get the next 15 (16 through 30):
 
 ```http
-POST https://contoso-search-eastus.search.windows.net/indexes/realestate-us-sample-index/docs/search?api-version=2025-09-01
+POST https://contoso-search-eastus.search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 
 {
-    "search": "condos with a view",
+    "search": "room with a view",
     "count": true,
     "top": 15,
     "skip": 15

@@ -81,7 +81,7 @@ The security filter efficiently matches the userIds, groupIds, and rbacScope fro
 
 ## Query example
 
-Here's an example of a query request from [sample code](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-ACL). The query token is passed in the request header. The query token is the personal access token of a user or a group identity behind the request.
+Here's an example of a query request from [sample code](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/acl). The query token is passed in the request header. The query token is the personal access token of a user or a group identity behind the request.
 
 ```http
 POST  {{endpoint}}/indexes/stateparks/docs/search?api-version=2025-11-01-preview

@@ -8,7 +8,7 @@ ms.author: heidist
 ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
-ms.topic: conceptual
+ms.topic: article
 ms.date: 06/20/2025
 ms.update-cycle: 365-days
 ---
@@ -83,7 +83,7 @@ Other elements are collapsed for brevity, but the following links provide detail
 
 A search document is defined by the "fields" collection in the body of [Create Index request](/rest/api/searchservice/indexes/create). You need fields for document identification (keys), storing searchable text, and fields for supporting filters, facets, and sorting. You might also need fields for data that a user never sees. For example, you might want fields for profit margins or marketing promotions that you can use in a scoring profile to boost a search score.
 
-If incoming data is hierarchical in nature, you can represent it within an index as a [complex type](search-howto-complex-data-types.md), used for nested structures. The built-in sample data set, Hotels, illustrates complex types using an Address (contains multiple subfields) that has a one-to-one relationship with each hotel, and a Rooms complex collection, where multiple rooms are associated with each hotel. 
+If incoming data is hierarchical in nature, you can represent it within an index as a [complex type](search-howto-complex-data-types.md), used for nested structures. The sample data set, [Hotels](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/hotels), illustrates complex types using an Address (contains multiple subfields) that has a one-to-one relationship with each hotel, and a Rooms complex collection, where multiple rooms are associated with each hotel. 
 
 <a name="index-attributes"></a>
 
@@ -118,29 +118,15 @@ You can monitor index size on the **Search management > Indexes** page in the Az
 The size of an index is determined by the:
 
 + Quantity and composition of your documents.
-+ Attributes on individual fields.
-+ Index configuration. Specifically, whether you include suggesters.
++ Attributes on individual fields: "retrievable" doesn't bloat your index, but "filterable", "sortable", "facetable" consume more storage for storing non-tokenized text.
++ Index configuration. Specifically, whether you include suggesters or specialized [analyzers](search-analyzers.md). If you use the edgeNgram tokenizer to store verbatim sequences of characters (`a, ab, abc, abcd`), the index is larger than if you use the standard analyzer.
 
-Document composition and quantity are determined by what you choose to import. Remember that a search index should only contain searchable content. If source data includes binary fields, omit those fields unless you're using AI enrichment to crack and analyze the content to create text-searchable information.
+Document composition and quantity are determined by what you choose to import. Remember that a search index should only contain content that's useful for your search application. If source data includes binary fields, omit those fields unless you're using AI enrichment to crack and analyze the content to create text-searchable information.
 
-Field attributes determine behaviors. To support those behaviors, the indexing process creates the necessary data structures. For example, for a field of type `Edm.String`, "searchable" invokes [full-text search](search-lucene-query-architecture.md), which scans inverted indexes for the tokenized term. In contrast, a "filterable" or "sortable" attribute supports iteration over unmodified strings. The example in the next section shows variations in index size based on the selected attributes.
+Field attributes determine behaviors. To support those behaviors, the indexing process creates the necessary data structures. For example, for a field of type `Edm.String`, "searchable" invokes [full-text search](search-lucene-query-architecture.md), which scans inverted indexes for the tokenized term. In contrast, a "filterable" or "sortable" attribute supports iteration over unmodified strings. 
 
 [**Suggesters**](index-add-suggesters.md) are constructs that support type-ahead or autocomplete queries. When you include a suggester, the indexing process creates the data structures necessary for verbatim character matches. Suggesters are implemented at the field level, so choose only those fields that are reasonable for type-ahead.
 
-### Example demonstrating the storage implications of attributes and suggesters
-
-The following screenshot illustrates index storage patterns resulting from various combinations of attributes. The index is based on the **real estate sample index**, which you can create easily using the Import data wizard and built-in sample data. Although the index schemas aren't shown, you can infer the attributes based on the index name. For example, *realestate-searchable* index has the "searchable" attribute selected and nothing else, *realestate-retrievable* index has the "retrievable" attribute selected and nothing else, and so forth.
-
-![Index size based on attribute selection](./media/search-what-is-an-index/realestate-index-size.png "Index size based on attribute selection")
-
-Although these index variants are somewhat artificial, we can refer to them for broad comparisons of how attributes affect storage:
-
-+ "retrievable" has no effect on index size.
-+ "filterable", "sortable", "facetable" consume more storage.
-+ **suggester** has a large potential for increasing index size, but not as much as the screenshot would indicate (all fields that could be made suggester-aware were selected, which isn't a likely scenario in most indexes).
-
-Also not reflected in the previous table is the effect of [analyzers](search-analyzers.md). If you use the edgeNgram tokenizer to store verbatim sequences of characters (`a, ab, abc, abcd`), the index is larger than if you use the standard analyzer.
-
 ## Basic operations and interaction
 
 Now that you have a better idea of what an index is, this section introduces index runtime operations, including connecting to and securing a single index.

@@ -40,7 +40,7 @@ Use a search client that supports preview APIs on the query request. You can use
 
 ## Spell correction with simple search
 
-The following example uses the built-in hotels-sample index to demonstrate spell correction on a simple text query. Without spell correction, the query returns zero results. With correction, the query returns one result for Johnson's family-oriented resort.
+The following example uses the [hotels-sample-index](search-get-started-portal.md) to demonstrate spell correction on a simple text query. Without spell correction, the query returns zero results. With correction, the query returns one result for Johnson's family-oriented resort.
 
 ```http
 POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-11-01-preview

@@ -80,11 +80,11 @@ items:
     items:
     - name: Create an agentic search pipeline
       href: get-started-portal-agentic-retrieval.md
-    - name: Create a search index
+    - name: Create an index for keyword search
       href: search-get-started-portal.md
-    - name: Create a vector index
+    - name: Create an index for vector search
       href: search-get-started-portal-import-vectors.md
-    - name: Create a multimodal index
+    - name: Create an index for multimodal search
       href: search-get-started-portal-image-search.md
     - name: Create a demo app
       href: search-create-app-portal.md

@@ -204,4 +204,4 @@ Content-Type: application/json
 
 ## Related content
 
-+ [https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-ACL](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/Quickstart-ACL)
++ [https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/acl](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/acl)

@@ -11,12 +11,12 @@ ms.devlang: csharp
 ms.custom:
   - ignite-2023
 ms.topic: tutorial
-ms.date: 07/10/2025
+ms.date: 12/05/2025
 ---
 
 # Create a search app in ASP.NET Core
 
-In this tutorial, you create a basic ASP.NET Core (Model-View-Controller) app that runs in localhost and connects to the hotels-sample-index on your search service. You learn how to:
+In this tutorial, you create a basic ASP.NET Core (Model-View-Controller) app that runs in localhost and connects to the [hotels-sample-index](search-get-started-portal.md) on your search service. You learn how to:
 
 > [!div class="checklist"]
 > + Create a basic search page

@@ -57,7 +57,7 @@ Learn about the latest updates to Azure AI Search functionality, docs, and sampl
 | [Scoring profiles for semantically ranked results](semantic-how-to-enable-scoring-profiles.md) | Generally available. |
 | [Truncate dimensions](vector-search-how-to-truncate-dimensions.md) | Generally available. |
 | [Unpack `@search.score` to view subscores in hybrid search results](hybrid-search-ranking.md#unpack-a-search-score-into-subscores) | Generally available. |
-| [Updates to import wizards (Phase 1)](search-import-data-portal.md) | The Azure portal is undergoing a three-phase rollout to unify the two import wizards. For Phase 1, the **Import and vectorize data** wizard has been renamed to **Import data (new)** and redeveloped to support keyword search, modernizing the legacy **Import data** workflow with an improved interface and user experience.<p>**Import data (new)** isn't a direct replacement for the old wizard. For example, it supports fewer skills for keyword search and doesn't offer built-in sample data.<p>Both wizards are currently available, but **Import data** will be deprecated in a future phase. |
+| [Updates to import wizards (Phase 1)](search-import-data-portal.md) | The Azure portal is undergoing a three-phase rollout to unify the two import wizards. For Phase 1, the **Import and vectorize data** wizard has been renamed to **Import data (new)** and redeveloped to support keyword search, modernizing the legacy **Import data** workflow with an improved interface and user experience.<p>**Import data (new)** isn't a direct replacement for the old wizard. For example, it supports fewer skills for keyword search.<p>Both wizards are currently available, but **Import data** will be deprecated in a future phase. |
 | [Support for Azure confidential computing](search-security-overview.md#data-in-use) | Configure [confidential computing](/azure/confidential-computing/use-cases-scenarios) during service creation to process data in use on confidential VMs. This compute type isn't intended for general use, but rather for stringent regulatory, compliance, or security requirements.<p>Confidential computing adds a 10% surcharge to the base cost of billable tiers. For more information, see the [pricing page](https://azure.microsoft.com/pricing/details/search/).<p>Now generally available through the 2025-05-01 version of [Services - Create or Update (REST API)](/rest/api/searchmanagement/services/create-or-update?view=rest-searchservice-2025-05-01&preserve-view=true) and the [Azure portal](search-create-service-portal.md#choose-a-compute-type). |
 
 ## August 2025