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Microsoft AI-102 Exam

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Question 171
DRAG DROP -
You have a web app that uses Azure Cognitive Search.
When reviewing billing for the app, you discover much higher than expected charges. You suspect that the query key is compromised.
You need to prevent unauthorized access to the search endpoint and ensure that users only have read only access to the documents collection. The solution must minimize app downtime.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Select and Place:
AI-102_171Q.png related to the Microsoft AI-102 Exam
Image AI-102_171R.png related to the Microsoft AI-102 Exam
Reference:
https://docs.microsoft.com/en-us/azure/search/search-security-api-keys

Question 172
You are developing an application that will use Azure Cognitive Search for internal documents.
You need to implement document-level filtering for Azure Cognitive Search.
Which three actions should you include in the solution? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Send Azure AD access tokens with the search request.
B. Retrieve all the groups.
C. Retrieve the group memberships of the user.
D. Add allowed groups to each index entry.
E. Create one index per group.
F. Supply the groups as a filter for the search requests.
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

Question 173
You have an Azure Cognitive Search solution and an enrichment pipeline that performs Sentiment Analysis on social media posts.
You need to define a knowledge store that will include the social media posts and the Sentiment Analysis results.
Which two fields should you include in the definition? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. storageContainer
B. storageConnectionString
C. files
D. tables
E. objects
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.
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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.

Question 174
SIMULATION -
Use the following login credentials as needed:
To enter your username, place your cursor in the Sign in box and click on the username below.
To enter your password, place your cursor in the Enter password box and click on the password below.
Azure Username: [email protected] -
Azure Password: XXXXXXXXXXXX -
The following information is for technical support purposes only:
Lab Instance: 12345678 -
Task -
You need to create an Azure resource named solution12345678 that will index a sample database named realestate-us-sample. The solution must ensure that users can search the index in English for people, organizations, and locations.
To complete this task, sign in to the Azure portal.
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.
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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.
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Reference:
https://docs.microsoft.com/en-us/azure/search/search-get-started-portal

Question 175
HOTSPOT
-
You create a knowledge store for Azure Cognitive Search by using the following JSON.
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Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.
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Image AI-102_175R.png related to the Microsoft AI-102 Exam


Question 176
You plan create an index for an Azure Cognitive Search service by using the Azure portal. The Cognitive Search service will connect to an Azure SQL database.
The Azure SQL database contains a table named UserMessages. Each row in UserMessages has a field named MessageCopy that contains the text of social media messages sent by a user.
Users will perform full text searches against the MessageCopy field, and the values of the field will be shown to the users.
You need to configure the properties of the index for the MessageCopy field to support the solution.
Which attributes should you enable for the field?
A. Sortable and Retrievable
B. Filterable and Retrievable
C. Searchable and Facetable
D. Searchable and Retrievable

Question 177
You have the following data sources:
• Finance: On-premises Microsoft SQL Server database
• Sales: Azure Cosmos DB using the Core (SQL) API
• Logs: Azure Table storage
• HR: Azure SQL database
You need to ensure that you can search all the data by using the Azure Cognitive Search REST API.
What should you do?
A. Export the data in Finance to Azure Data Lake Storage.
B. Configure multiple read replicas for the data in Sales.
C. Ingest the data in Logs into Azure Data Explorer.
D. Migrate the data in HR to Azure Blob storage.

Question 178
You are building a multilingual chatbot.
You need to send a different answer for positive and negative messages.
Which two Text Analytics APIs should you use? Each correct answer presents part of the solution. (Choose two.)
NOTE: Each correct selection is worth one point.
A. Linked entities from a well-known knowledge base
B. Sentiment Analysis
C. Key Phrases
D. Detect Language
E. Named Entity Recognition
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

Question 179
You build a bot by using the Microsoft Bot Framework SDK and the Azure Bot Service.
You plan to deploy the bot to Azure.
You register the bot by using the Bot Channels Registration service.
Which two values are required to complete the deployment? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. botId
B. tenantId
C. appId
D. objectId
E. appSecret
Reference:
https://github.com/MicrosoftDocs/bot-docs/blob/live/articles/bot-service-quickstart-registration.md

Question 180
HOTSPOT -
You are building a chatbot by using the Microsoft Bot Framework Composer.
You have the dialog design shown in the following exhibit.
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For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Hot Area:
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Image AI-102_180R.png related to the Microsoft AI-102 Exam
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