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.
DE
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":"
"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.
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.
The type of projection you specify in this structure determines the type of storage used by knowledge store, but not its structure. Fields in tables, objects, and files are determined by Shaper skill output if you're creating the knowledge store programmatically, or by the Import data wizard if you're using the portal. - objects project JSON document into Blob storage. The physical representation of an object is a hierarchical JSON structure that represents an enriched document.
Agree with you, thanks for explanation
BE is the answer
I agree. There seems to not have a need for tables.
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.
I agree, as the task is to define a knowledge store and not the potential prohjections that define the format in which the enriched data is saved
BD 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.
The type of projection you specify in this structure determines the type of storage used by knowledge store, but not its structure. Fields in tables, objects, and files are determined by Shaper skill output if you're creating the knowledge store programmatically, or by the Import data wizard if you're using the portal. - objects project JSON document into Blob storage. The physical representation of an object is a hierarchical JSON structure that represents an enriched document.
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.
I would choose table projection over object as it will be easier to analyze the data later. A full JSON representation of your data and enrichments in one JSON document, in this case, is not doing you any good other than more work required for later analysis.
Why would you put social media posts and the Sentiment Analysis results in one JSON document to make your later work more difficult?
Behind the scenes, table projection stored data in Azure Table Storage, where scalability and performance of the storage becomes vital to deal with when unstructured data like social media post is stored. By design, table storages should not be used to store objects which can be of very big in size and can be extremely difficult to apply search pattern on. Check this out: The scalability and performance targets listed here are high-end targets, but are achievable. In all cases, the request rate and bandwidth achieved by your storage account depends upon the size of objects stored, the access patterns utilized, and the type of workload your application performs. ref: https://learn.microsoft.com/en-us/azure/storage/tables/scalability-targets
https://learn.microsoft.com/en-us/azure/storage/tables/scalability-targets
To me correct answer is BE https://learn.microsoft.com/en-us/azure/search/knowledge-store-concept-intro?tabs=portal#knowledge-store-definition
A modified version of this was in the exam today.
storageConnectionString and Object.
why not "file"??
Enriched contented is projected to tables: https://learn.microsoft.com/en-us/azure/search/knowledge-store-concept-intro?tabs=portal#knowledge-store-definition
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
AB: We need storage to upload data and connection string. https://learn.microsoft.com/en-us/azure/search/knowledge-store-create-rest
It is obvious that BE is the correct answer.
I say this answer is B and E.
was on exam 20.06.2024.
Selected Answer: BE