Win IT Exam with Last Dumps 2024

Reference:
https://docs.microsoft.com/en-us/azure/search/search-security-api-keys

Your documents must include a field specifying which groups have access. This information becomes the filter criteria against which documents are selected or rejected from the result set returned to the issuer.
D: A query request targets the documents collection of a single index on a search service.
CF: In order to trim documents based on group_ids access, you should issue a search query with a group_ids/any(g:search.in(g, 'group_id1, group_id2,...')) filter, where 'group_id1, group_id2,...' are the groups to which the search request issuer belongs.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-security-trimming-for-azure-search

Knowledge store definition -
A knowledge store is defined inside a skillset definition and it has two components:
A connection string to Azure Storage
Projections that determine whether the knowledge store consists of tables, objects or files.
The projections element is an array. You can create multiple sets of table-object-file combinations within one knowledge store.
"knowledgeStore": {
"storageConnectionString":"<YOUR-AZURE-STORAGE-ACCOUNT-CONNECTION-STRING>",
"projections":[
{
"tables":[ ],
"objects":[ ],
"files":[ ]
}
}
The type of projection you specify in this structure determines the type of storage used by knowledge store.
Objects - project JSON document into Blob storage. The physical representation of an object is a hierarchical JSON structure that represents an enriched document.
Tables - project enriched content into Table Storage. Define a table projection when you need tabular reporting structures for inputs to analytical tools or export as data frames to other data stores. You can specify multiple tables within the same projection group to get a subset or cross section of enriched documents. Within the same projection group, table relationships are preserved so that you can work with all of them.
Projected content is not aggregated or normalized. The following screenshot shows a table, sorted by key phrase, with the parent document indicated in the adjacent column. In contrast with data ingestion during indexing, there is no linguistic analysis or aggregation of content. Plural forms and differences in casing are considered unique instances.

Incorrect:
Not C: files - project image files into Blob storage. A file is an image extracted from a document, transferred intact to Blob storage. Although it is named "files", it shows up in Blob Storage, not file storage.

Step 1 - Start the Import data wizard and create a data source
1. Sign in to the Azure portal with your Azure account.
2. Find your search service and on the Overview page, click Import data on the command bar to create and populate a search index.

3. In the wizard, click Connect to your data, and select the sample database named realestate-us-sample
Step 2 - Skip the "Enrich content" page
The wizard supports the creation of an AI enrichment pipeline for incorporating the Cognitive Services AI algorithms into indexing.
We'll skip this step for now, and move directly on to Customize target index.
Step 3 - Configure index -
The solution must ensure that users can search the index in English for people, organizations, and locations.
Configure Searchable for the fields people, organizations, and locations.

Reference:
https://docs.microsoft.com/en-us/azure/search/search-get-started-portal

B: The Text Analytics API's Sentiment Analysis feature provides two ways for detecting positive and negative sentiment. If you send a Sentiment Analysis request, the API will return sentiment labels (such as "negative", "neutral" and "positive") and confidence scores at the sentence and document-level.
D: The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and returns language identifiers with a score that indicates the strength of the analysis.
This capability is useful for content stores that collect arbitrary text, where language is unknown.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-sentiment-analysis?tabs=version-3-1
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-language-detection

Reference:
https://github.com/MicrosoftDocs/bot-docs/blob/live/articles/bot-service-quickstart-registration.md

Box 1: No -
User.name is a property.
Box 2: Yes -
Box 3: Yes -
The coalesce() function evaluates a list of expressions and returns the first non-null (or non-empty for string) expression.
Reference:
https://docs.microsoft.com/en-us/composer/concept-language-generation
https://docs.microsoft.com/en-us/azure/data-explorer/kusto/query/coalescefunction