Scenario: Support autocompletion and autosuggestion based on all product name variants.
A: Call a suggester-enabled query, in the form of a Suggestion request or Autocomplete request, using an API. API usage is illustrated in the following call to the Autocomplete REST API.
POST /indexes/myxboxgames/docs/autocomplete?search&api-version=2020-06-30
{
"search": "minecraf",
"suggesterName": "sg"
}
B: In Azure Cognitive Search, typeahead or "search-as-you-type" is enabled through a suggester. A suggester provides a list of fields that undergo additional tokenization, generating prefix sequences to support matches on partial terms. For example, a suggester that includes a City field with a value for "Seattle" will have prefix combinations of "sea", "seat", "seatt", and "seattl" to support typeahead.
F: Use the default standard Lucene analyzer ("analyzer": null) or a language analyzer (for example,
"analyzer": "en.Microsoft") on the field.
Reference:
https://docs.microsoft.com/en-us/azure/search/index-add-suggesters

The wiki contains text in English, French and Portuguese.
Scenario: All planned projects must support English, French, and Portuguese.
The Document Extraction skill extracts content from a file within the enrichment pipeline. This allows you to take advantage of the document extraction step that normally happens before the skillset execution with files that may be generated by other skills.
Note: The Translator Text API will be used to determine the from language. The Language detection skill is not required.
Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-skill-document-extraction
https://docs.microsoft.com/en-us/azure/search/cognitive-search-skill-text-translation

Explanation:

You are using Azure Cognitive Search, where access is controlled by:
* Admin keys: Provide full read/write control (never given to apps).
* Query keys: Provide read-only access, meant for client apps.
Here, the query key has been compromised. You want to minimize downtime and ensure continued read-only access.
* First, generate a new query key from the Azure portal or via REST API.
* This allows you to continue providing read-only access to authorized apps.
* Update the application configuration so that it authenticates requests with the new query key.
* This ensures uninterrupted service while preparing to retire the compromised key.
* Once the app is using the new key successfully, revoke the compromised query key.
* This prevents further unauthorized usage.
* Regenerate primary/secondary admin key: Not necessary since only the query key is compromised, and admin keys give full control.
* Change app to use secondary admin key: Insecure (admin keys should never be exposed to client apps).
* Add a new query key.
* Change the app to use the new key.
* Delete the compromised key.
* Manage admin and query keys in Azure Cognitive Search
* Create and use query keys

Reference:
You are building a LUIS (Language Understanding) model. You want to add more contributors.
Options Review:
Conditional access policy in AAD (A): Controls sign-in/access security, not contributors.
Access control (IAM) for prediction resource (C): The prediction resource is for runtime queries, not authoring. Contributors are not added here.
Access control (IAM) for authoring resource (B): Correct. Authoring resources control who can edit/train
/publish models. You add contributors here.
The answer: B. the Access control (IAM) page for the authoring resources in the Azure portal Reference:Assign roles in LUIS

https://learn.microsoft.com/en-us/azure/cognitive-services/language-service/named-entity-recognition
/overview Named Entity Recognition (NER) is one of the features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. The NER feature can identify and categorize entities in unstructured text. For example: people, places, organizations, and quantities.