You are developing the knowledgebase by using Azure Cognitive Search. You need to process wiki content to meet the technical requirements. What should you include in the solution?
A.
an indexer for Azure Blob storage attached to a skillset that contains the language detection skill and the text translation skill
B.
an indexer for Azure Blob storage attached to a skillset that contains the language detection skill
C.
an indexer for Azure Cosmos DB attached to a skillset that contains the document extraction skill and the text translation skill
D.
an indexer for Azure Cosmos DB attached to a skillset that contains the language detection skill and the text translation skill
The correct answer is D. Use an indexer connected to Azure Cosmos DB that includes language detection and text translation skills. This solution meets the requirement for handling multiple languages and supports content transformation for English, French, and Portuguese by using the text translation skill, which aligns with the technical requirement for multilingual support. Additionally, using Azure Cosmos DB and associated skill sets ensures content security and role-based access control (RBAC), meeting the requirements for content approval and security.
This is not correct.
Azure Cosmos DB is a globally distributed multi-model database with support for multiple APIs.
The Get Document operation retrieves a document by its partition key and document key.
Method Request URI Description
GET https://{databaseaccount}.documents.azure.com/dbs/{db-id}/colls/{coll-id}/docs/{doc-id} Note that the {databaseaccount} is the name of the Azure Cosmos DB account created under your subscription. The {db-id} value is the user generated name/ID of the database, not the system generated ID (rid). The {coll-id} value is the name of the collection. The {doc-id} value is the ID of the document to be retrieved.
https://learn.microsoft.com/en-us/rest/api/cosmos-db/get-a-document
Is this question checking if I can spot in the table that the wiki content is kept in CosmosDB and not in Blob storage? Is that the skill an AI-engineer should possess? |
Next level is to know that the data in cosmosDB stored for wiki are not documents or images. Just assume based on language skills?
Therefore, A. an indexer for Cosmos DB attached to a skillset that contains the language detection skill and the text translation skill aligns with the technical requirements for content approval, multilingual support, and RBAC1
Don't foget the requirement where it says the searchable knowledgebase should contain all intellectual property. Another argument for A since Azure Cosmos DB is typically used for structured or semi-structured data, not for handling diverse formats like video or audio.
Windows Copilot:
B. An indexer for Azure Blob storage attached to a skillset that contains the language detection skill.
Here’s the explanation:
Azure Blob Storage: You’ll use Azure Blob storage to store your content, including wiki articles and other relevant documents.
Indexer: An indexer in Azure Cognitive Search automatically discovers new content from supported data sources (such as blob storage) and adds it to the search index. In your case, you’ll create an indexer to process the wiki content.
Skillset: A skillset defines a set of cognitive skills (such as language detection, text translation, and more) that can be applied during indexing. Since your knowledgebase needs to support multiple languages (English, French, and Portuguese), you’ll attach a skillset to the indexer.
...
Language Detection Skill: This skill detects the language of the content. It ensures that the appropriate language-specific processing (such as translation) can be applied.
By using the language detection skill, you’ll be able to handle content in different languages and transcribe jargon accurately. Additionally, the Azure Cognitive Search service supports full-text search, semantic search, vector search, and hybrid search, which aligns with your requirements for searching content in various formats, including video.
Remember that the semantic search and vector search features are currently in public preview in Azure Cognitive Search. The solution will also provide relevant links to external resources for further research, enhancing the overall knowledgebase experience. 📚🔍🌐
For more details, you can refer to the official documentation.
(1) Search and query an enterprise knowledge base by using Azure OpenAI or .... https://learn.microsoft.com/en-us/azure/architecture/ai-ml/openai/idea/search-and-query-using-openai-service.
(2) Create a knowledge store with Azure AI Search - Training. https://learn.microsoft.com/en-us/training/modules/create-knowledge-store-azure-cognitive-search/.
(3) Implement knowledge mining with Azure Cognitive Search. https://learn.microsoft.com/en-us/training/paths/implement-knowledge-mining-azure-cognitive-search/.
(4) Knowledge store concepts - Azure AI Search | Microsoft Learn. https://learn.microsoft.com/en-us/azure/search/knowledge-store-concept-intro.
(5) Index file content and metadata by using Azure Cognitive Search. https://learn.microsoft.com/en-us/azure/architecture/ai-ml/architecture/search-blob-metadata.
It is confusing because the table mentions wikis are in Text format, but on the other hand, wikis (and blog entries) usually contain HTML.
If they do contain HTML is should be C (extract text from html - dont translate tags)
If they don't it should be D
At the end I choose D because we shouldn't assume stuff, the questions says "Text" not "Text/HTML"
IMHO the correct answer should be D.
You don't need Document Extraction to extract text from files. You have already the text in wikis.
https://learn.microsoft.com/en-us/azure/search/cognitive-search-skill-document-extraction
It's true that Text Translation could also detect the source language but reading the documentation seems it could be not so accurate.
https://learn.microsoft.com/en-us/azure/search/cognitive-search-skill-text-translation
For sure you need two operations here: detect and translate.
Wikis are already in text format and available in three languages so what do you need the document extraction and translation normalize the text to a single language before indexing for? What you need is to detect the language of the text and translate it to English if you want to normalize the text to a single language before indexing for search. Only in this case it would make sense to use text translation skill.
Correction: Wikis are already in text format and available in three languages so what do you need the document extraction and translation for? What you need is to detect the language of the text and translate it to English if you want to normalize the text to a single language before indexing for search. Only in this case it would make sense to use text translation skill.
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