picked up some acrolinx suggestions

Author: HeidiSteen

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

@@ -74,7 +74,7 @@ You are now ready to move on the Import data wizard.
 
 Next, configure AI enrichment to invoke language detection, text translation, and entity recognition. 
 
-1. For this quickstart, we are using the **Free** Cognitive Services resource. The sample data consists of 10 files, so the daily, per-indexer allotment of 20 free transactions on Cognitive Services is sufficient for this quickstart. 
+1. For this quickstart, you can use the **Free** Cognitive Services resource. The sample data consists of 10 files, so the daily, per-indexer allotment of 20 free transactions on Cognitive Services is sufficient for this quickstart. 
 
    :::image type="content" source="media/cognitive-search-quickstart-blob/free-enrichments.png" alt-text="Attach free Cognitive Services processing" border="true":::
 
@@ -104,7 +104,7 @@ For this quickstart, the wizard does a good job setting reasonable defaults:
 
   :::image type="content" source="media/cognitive-search-quickstart-blob/index-fields-lang-entities.png" alt-text="Index fields" border="true":::
 
-Marking a field as **Retrievable** does not mean that the field *must* be present in the search results. You can precisely control search results composition by using the **$select** query parameter to specify which fields to include. For text-heavy fields like `content`, the **$select** parameter is your solution for shaping manageable search results to the human users of your application, while ensuring client code has access to all the information it needs via the **Retrievable** attribute.
+Marking a field as **Retrievable** doesn't mean that the field *must* be present in the search results. You can precisely control search results composition by using the **$select** query parameter to specify which fields to include. For text-heavy fields like `content`, the **$select** parameter is your solution for shaping manageable search results to the human users of your application, while ensuring client code has access to all the information it needs via the **Retrievable** attribute.
 
 ### Step 4 - Configure the indexer
 
@@ -151,7 +151,7 @@ When you're working in your own subscription, it's a good idea at the end of a p
 
 You can find and manage resources in the portal, using the **All resources** or **Resource groups** link in the left-navigation pane.
 
-If you are using a free service, remember that you are limited to three indexes, indexers, and data sources. You can delete individual items in the portal to stay under the limit. 
+If you're using a free service, remember that you're limited to three indexes, indexers, and data sources. You can delete individual items in the portal to stay under the limit. 
 
 ## Next steps
 

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

@@ -53,7 +53,7 @@ In the following steps, set up a blob container in Azure Storage to store hetero
 
 You should have 10 files containing photographs of signs.
 
-There is a second subfolder that includes landmark buildings. If you want to [attach a Cognitive Services key](cognitive-search-attach-cognitive-services.md), you can include these files as well to see how image analysis works over image files that do not include embedded text. The key is necessary for jobs that exceed the free allotment.
+There is a second subfolder that includes landmark buildings. If you want to [attach a Cognitive Services key](cognitive-search-attach-cognitive-services.md), you can include these files as well to see how image analysis works over image files that don't include embedded text. The key is necessary for jobs that exceed the free allotment.
 
 You are now ready to move on the Import data wizard.
 
@@ -75,7 +75,7 @@ You are now ready to move on the Import data wizard.
 
 Next, configure AI enrichment to invoke OCR and image analysis. 
 
-1. For this quickstart, we are using the **Free** Cognitive Services resource. The sample data consists of 19 files, so the daily, per-indexer allotment of 20 free transactions on Cognitive Services is sufficient for this quickstart. 
+1. For this quickstart, you can use the **Free** Cognitive Services resource. The sample data consists of 19 files, so the daily, per-indexer allotment of 20 free transactions on Cognitive Services is sufficient for this quickstart. 
 
    :::image type="content" source="media/cognitive-search-quickstart-blob/free-enrichments.png" alt-text="Attach free Cognitive Services processing" border="true":::
 
@@ -103,7 +103,7 @@ For this quickstart, the wizard does a good job setting reasonable defaults:
 
   :::image type="content" source="media/cognitive-search-quickstart-blob/index-fields-ocr-images.png" alt-text="Index fields" border="true":::
 
-Marking a field as **Retrievable** does not mean that the field *must* be present in the search results. You can precisely control search results composition by using the **$select** query parameter to specify which fields to include. For text-heavy fields like `content`, the **$select** parameter is your solution for shaping manageable search results to the human users of your application, while ensuring client code has access to all the information it needs via the **Retrievable** attribute.
+Marking a field as **Retrievable** doesn't mean that the field *must* be present in the search results. You can precisely control search results composition by using the **$select** query parameter to specify which fields to include. For text-heavy fields like `content`, the **$select** parameter is your solution for shaping manageable search results to the human users of your application, while ensuring client code has access to all the information it needs via the **Retrievable** attribute.
 
 ### Step 4 - Configure the indexer
 
@@ -151,7 +151,7 @@ When you're working in your own subscription, it's a good idea at the end of a p
 
 You can find and manage resources in the portal, using the **All resources** or **Resource groups** link in the left-navigation pane.
 
-If you are using a free service, remember that you are limited to three indexes, indexers, and data sources. You can delete individual items in the portal to stay under the limit. 
+If you're using a free service, remember that you're limited to three indexes, indexers, and data sources. You can delete individual items in the portal to stay under the limit. 
 
 ## Next steps
 

articles/search/search-what-is-azure-search.md

@@ -39,11 +39,11 @@ On the search service itself, the two primary workloads are *indexing* and *quer
 
   Additionally, if your content includes mixed files, you have the option of adding *AI enrichment* through [cognitive skills](cognitive-search-working-with-skillsets.md). AI enrichment can extract text embedded in application files, and also infer text and structure from non-text files by analyzing the content. 
 
-  The skills providing the analysis are predefined ones from Microsoft, or custom skills that you create. The subsequent analysis and transformations can result in new information and structures that did not previously exist, providing high utility for many search and knowledge mining scenarios.
+  The skills providing the analysis are predefined ones from Microsoft, or custom skills that you create. The subsequent analysis and transformations can result in new information and structures that didn't previously exist, providing high utility for many search and knowledge mining scenarios.
 
 + [**Querying**](search-query-overview.md) can happen once an index is populated with searchable text, when your client app sends query requests to a search service and handles responses. All query execution is over a search index that you create, own, and store in your service. In your client app, the search experience is defined using APIs from Azure Cognitive Search, and can include relevance tuning, autocomplete, synonym matching, fuzzy matching, pattern matching, filter, and sort.
 
-Functionality is exposed through a simple [REST API](/rest/api/searchservice/), or Azure SDKs like the [Azure SDK for .Net](search-howto-dotnet-sdk.md), that masks the inherent complexity of information retrieval. You can also use the Azure portal for service administration and content management, with tools for prototyping and querying your indexes and skillsets. Because the service runs in the cloud, infrastructure and availability are managed by Microsoft.
+Functionality is exposed through a simple [REST API](/rest/api/searchservice/), or Azure SDKs like the [Azure SDK for .NET](search-howto-dotnet-sdk.md), that masks the inherent complexity of information retrieval. You can also use the Azure portal for service administration and content management, with tools for prototyping and querying your indexes and skillsets. Because the service runs in the cloud, infrastructure and availability are managed by Microsoft.
 
 ## Why use Cognitive Search?
 
@@ -90,8 +90,8 @@ Customers often ask how Azure Cognitive Search compares with other search-relate
 |-------------|-----------------|
 | Microsoft Search | [Microsoft Search](/microsoftsearch/overview-microsoft-search) is for Microsoft 365 authenticated users who need to query over content in SharePoint. It's offered as a ready-to-use search experience, enabled and configured by administrators, with the ability to accept external content through connectors from Microsoft and other sources. If this describes your scenario, then Microsoft Search with Microsoft 365 is an attractive option to explore.<br/><br/>In contrast, Azure Cognitive Search executes queries over an index that you define, populated with data and documents you own, often from diverse sources. Azure Cognitive Search has crawler capabilities for some Azure data sources through [indexers](search-indexer-overview.md), but you can push any JSON document that conforms to your index schema into a single, consolidated searchable resource. You can also customize the indexing pipeline to include machine learning and lexical analyzers. Because Cognitive Search is built to be a plug-in component in larger solutions, you can integrate search into almost any app, on any platform.|
 |Bing | [Bing Web Search API](../cognitive-services/bing-web-search/index.yml) searches the indexes on Bing.com for matching terms you submit. Indexes are built from HTML, XML, and other web content on public sites. Built on the same foundation, [Bing Custom Search](/azure/cognitive-services/bing-custom-search/) offers the same crawler technology for web content types, scoped to individual web sites.<br/><br/>In Cognitive Search, you can define and populate the index. You can use [indexers](search-indexer-overview.md) to crawl data on Azure data sources, or push any index-conforming JSON document to your search service. |
-|Database search | Many database platforms include a built-in search experience. SQL Server has [full text search](/sql/relational-databases/search/full-text-search). Cosmos DB and similar technologies have queryable indexes. When evaluating products that combine search and storage, it can be challenging to determine which way to go. Many solutions use both: DBMS for storage, and Azure Cognitive Search for specialized search features.<br/><br/>Compared to DBMS search, Azure Cognitive Search stores content from heterogeneous sources and offers specialized text processing features such as linguistic-aware text processing (stemming, lemmatization, word forms) in [56 languages](/rest/api/searchservice/language-support). It also supports autocorrection of misspelled words, [synonyms](/rest/api/searchservice/synonym-map-operations), [suggestions](/rest/api/searchservice/suggestions), [scoring controls](/rest/api/searchservice/add-scoring-profiles-to-a-search-index), [facets](search-faceted-navigation.md),  and [custom tokenization](/rest/api/searchservice/custom-analyzers-in-azure-search). The [full text search engine](search-lucene-query-architecture.md) in Azure Cognitive Search is built on Apache Lucene, an industry standard in information retrieval. However, while Azure Cognitive Search persists data in the form of an inverted index, it is not a replacement for true data storage and we don't recommend using it in that capacity. For more information, see this [forum post](https://stackoverflow.com/questions/40101159/can-azure-search-be-used-as-a-primary-database-for-some-data). <br/><br/>Resource utilization is another inflection point in this category. Indexing and some query operations are often computationally intensive. Offloading search from the DBMS to a dedicated solution in the cloud preserves system resources for transaction processing. Furthermore, by externalizing search, you can easily adjust scale to match query volume.|
-|Dedicated search solution | Assuming you have decided on dedicated search with full spectrum functionality, a final categorical comparison is between on premises solutions or a cloud service. Many search technologies offer controls over indexing and query pipelines, access to richer query and filtering syntax, control over rank and relevance, and features for self-directed and intelligent search. <br/><br/>A cloud service is the right choice if you want a turn-key solution with minimal overhead and maintenance, and adjustable scale. <br/><br/>Within the cloud paradigm, several providers offer comparable baseline features, with full-text search, geospatial search, and the ability to handle a certain level of ambiguity in search inputs. Typically, it's a [specialized feature](search-features-list.md), or the ease and overall simplicity of APIs, tools, and management that determines the best fit. |
+|Database search | Many database platforms include a built-in search experience. SQL Server has [full text search](/sql/relational-databases/search/full-text-search). Cosmos DB and similar technologies have queryable indexes. When evaluating products that combine search and storage, it can be challenging to determine which way to go. Many solutions use both: DBMS for storage, and Azure Cognitive Search for specialized search features.<br/><br/>Compared to DBMS search, Azure Cognitive Search stores content from heterogeneous sources and offers specialized text processing features such as linguistic-aware text processing (stemming, lemmatization, word forms) in [56 languages](/rest/api/searchservice/language-support). It also supports autocorrection of misspelled words, [synonyms](/rest/api/searchservice/synonym-map-operations), [suggestions](/rest/api/searchservice/suggestions), [scoring controls](/rest/api/searchservice/add-scoring-profiles-to-a-search-index), [facets](search-faceted-navigation.md),  and [custom tokenization](/rest/api/searchservice/custom-analyzers-in-azure-search). The [full text search engine](search-lucene-query-architecture.md) in Azure Cognitive Search is built on Apache Lucene, an industry standard in information retrieval. However, while Azure Cognitive Search persists data in the form of an inverted index, it isn't a replacement for true data storage and we don't recommend using it in that capacity. For more information, see this [forum post](https://stackoverflow.com/questions/40101159/can-azure-search-be-used-as-a-primary-database-for-some-data). <br/><br/>Resource utilization is another inflection point in this category. Indexing and some query operations are often computationally intensive. Offloading search from the DBMS to a dedicated solution in the cloud preserves system resources for transaction processing. Furthermore, by externalizing search, you can easily adjust scale to match query volume.|
+|Dedicated search solution | Assuming you've decided on dedicated search with full spectrum functionality, a final categorical comparison is between on premises solutions or a cloud service. Many search technologies offer controls over indexing and query pipelines, access to richer query and filtering syntax, control over rank and relevance, and features for self-directed and intelligent search. <br/><br/>A cloud service is the right choice if you want a turn-key solution with minimal overhead and maintenance, and adjustable scale. <br/><br/>Within the cloud paradigm, several providers offer comparable baseline features, with full-text search, geospatial search, and the ability to handle a certain level of ambiguity in search inputs. Typically, it's a [specialized feature](search-features-list.md), or the ease and overall simplicity of APIs, tools, and management that determines the best fit. |
 
 Among cloud providers, Azure Cognitive Search is strongest for full text search workloads over content stores and databases on Azure, for apps that rely primarily on search for both information retrieval and content navigation.