Exam AI-102 topic 4 question 11 discussion

Typo, BE is the answer. https://learn.microsoft.com/en-us/azure/search/knowledge-store-concept-intro?tabs=portal#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.

To define a knowledge store in Azure Cognitive Search that includes both the social media posts and the Sentiment Analysis results, you should include the following two fields in the definition: A. storageContainer: This field specifies the Azure Blob Storage container where the enriched data will be stored. You need to define a storage container to hold the processed data from the enrichment pipeline. B. storageConnectionString: This field provides the connection string to the Azure Storage account that will be used to store the enriched data. The connection string is necessary for Azure Cognitive Search to connect and store the data in the specified storage account. Both the storageContainer and storageConnectionString fields are required to set up a knowledge store in Azure Cognitive Search that can store the social media posts and the Sentiment Analysis results.

Correct answers: A. storageContainer Specifies the Azure Blob Storage container where enriched output will be stored. D. tables Used to define structured outputs (like sentiment analysis results) in table format for downstream querying. Why not the others? B. storageConnectionString This is part of the cognitive search skillset or pipeline configuration, not the knowledge store definition itself. C. files Used for raw file output like images or PDFs, not ideal for structured data like social posts and sentiment analysis. E. objects Used when outputting JSON objects, but not specifically required for the typical structure of a sentiment analysis pipeline

https://learn.microsoft.com/en-us/azure/search/knowledge-store-concept-intro?tabs=portal#knowledge-store-definition A knowledge store is defined inside a skillset definition and it has two components: A connection string to Azure Storage --> B is correct https://learn.microsoft.com/en-us/azure/synapse-analytics/machine-learning/tutorial-cognitive-services-sentiment A user in Azure Synapse can select a table that contains a text column to enrich with sentiments. These sentiments can be positive, negative, mixed, or neutral. --> This makes D correct BD to me

There is another question where the user case is to store social media posts in tables.

To define a knowledge store that includes both the social media posts and the Sentiment Analysis results, you should include the following two fields: B. storageConnectionString D. tables These fields will allow you to store the analyzed data in a structured format and connect to the storage service.

BE is the answer

To define a knowledge store that includes social media posts and Sentiment Analysis results, you should include the following fields: -tables: This field is used to store structured data, such as the results of the Sentiment Analysis. -objects: This field is used to store unstructured data, such as the social media posts themselves. StorageConnectionString is not a knowledge store. It can't be B.

Selected Answer: BE

was on exam 20.06.2024.

I say this answer is B and E.

It is obvious that BE is the correct answer.

AB: We need storage to upload data and connection string. https://learn.microsoft.com/en-us/azure/search/knowledge-store-create-rest

AB https://learn.microsoft.com/en-us/azure/search/knowledge-store-create-rest https://learn.microsoft.com/en-us/azure/search/knowledge-store-create-rest#create-a-data-source

storageConnectionString and Object.

For the need to define a knowledge store that includes social media posts and the Sentiment Analysis results, the most relevant fields/types to include in your definition would likely be: D. tables: For storing structured data such as the original posts along with their sentiment scores in a structured, queryable format. E. objects: For preserving the full, enriched data set in its original format along with nested Sentiment Analysis results.

Enriched contented is projected to tables: https://learn.microsoft.com/en-us/azure/search/knowledge-store-concept-intro?tabs=portal#knowledge-store-definition