Exam AI-102 topic 1 question 25 discussion

Question says : ..."You need to configure an enrichment pipeline to perform optical character recognition (OCR) and "text analytics"... Just because of this second requirement Answer is a Multi Cognitive Service (D), alone vision service (=OCR wont make any text analytics, text extraction is not a text analytics !).. Read here : https://learn.microsoft.com/en-us/azure/search/cognitive-search-attach-cognitive-services?tabs=portal

For processing 50,000 documents with OCR and text analytics in an enrichment pipeline, while still aiming to minimize costs, a more practical approach would be: D. a new Cognitive Services resource that uses the S0 pricing tier This option is more suitable for several reasons: Capacity and Scalability: The S0 pricing tier offers a higher transaction limit, making it more suitable for processing a large volume of documents like 50,000. It can handle the scale of operations required for this task without hitting the cap as quickly as the free tier might. Cost Efficiency at Scale: While the S0 tier incurs costs, it is designed to be cost-effective for medium to large-scale operations. By carefully managing the use of resources and optimizing the processing pipeline, it's possible to keep costs under control while meeting the project's requirements.

https://learn.microsoft.com/en-us/azure/search/cognitive-search-attach-cognitive-services?tabs=portal The S0 pricing tier offers a higher transaction limit, which makes it suitable for handling a large volume of documents efficiently. This option ensures that the required processing can be performed without the limitations of the free tier, and it remains cost-effective for medium to large-scale operations. Answer is D

I checked with many LLM services and get answer B: a free (Limited enrichments) Cognitive Services resource

Copilot says A. a new Computer Vision resource Explanation: To perform optical character recognition (OCR) on scanned documents, you would need to use the Computer Vision service, which is part of Azure Cognitive Services. This service can extract printed and handwritten text from images and documents. It's also capable of extracting rich information from images to categorize and process visual data. The Text Analytics service, also part of Azure Cognitive Services, can be used for processing the text once it's extracted, but the question specifically asks about the OCR part of the pipeline, so the Computer Vision service is the correct choice. The cost would depend on the volume of data processed, but using a dedicated Computer Vision resource is likely to be more cost-effective than using a general Cognitive Services resource or an Azure Machine Learning Designer pipeline. The free tier of Cognitive Services is not suitable for processing a large volume of documents like 50,000.

A Multiservice account is required since both OCR and text analytics are required. Since a multiservice account does not support the free tier (F0), then B is not a valid option. So, the answer has to be D.

Use S0 SKU

D is right.

Given the goal of minimizing costs while performing OCR and text analytics on a collection of 50,000 scanned documents, and considering that the Limited enrichments tier offers basic enrichments at no additional cost, the most suitable choice is indeed: B. a free (Limited enrichments) Cognitive Services resource.

B. a free (Limited enrichments) Cognitive Services resource Explanation: The free (Limited enrichments) tier of Cognitive Services provides access to Optical Character Recognition (OCR) and basic text analytics capabilities. Attaching this Cognitive Services resource to the skillset allows you to perform OCR and text analytics on the scanned documents. Since the requirement is to minimize costs, choosing the free tier is the most cost-effective option. This option aligns with the goal of making the text available through Azure Cognitive Search while keeping costs low.

Correct option is D - a new Cognitive Services resource that uses the S0 pricing tier We can't do this with free tier, thus we can't select Option B

to minimize cost you would not use a S0 tier which is why the answer is A

OCR is a built-in skillset that required billable tier of Azure AI Search, so the D is correct

correct answer is D because you need to support a multiservice resource and it cannot be free.

D is the answer. https://learn.microsoft.com/en-us/azure/search/cognitive-search-attach-cognitive-services?tabs=portal When configuring an optional AI enrichment pipeline in Azure Cognitive Search, you can enrich a limited number of documents free of charge. For larger and more frequent workloads, you should attach a billable multi-service Cognitive Services resource. A multi-service resource references "Cognitive Services" as the offering, rather than individual services, with access granted through a single API key. This key is specified in a skillset and allows Microsoft to charge you for using these APIs: - Computer Vision for image analysis and optical character recognition (OCR) - Language service for language detection, entity recognition, sentiment analysis, and key phrase extraction - Translator for machine text translation

Based on the information from the official Azure documentation, the most cost-effective way to configure an enrichment pipeline for OCR and text analytics in Azure Cognitive Search would be to use a billable Cognitive Services resource. This is because built-in skills, such as OCR and text analytics, are based on the Cognitive Services APIs and unless your content input is small, you would need to attach a billable Cognitive Services resource to run larger workloads. Therefore, the correct answer to your question would be: D. a new Cognitive Services resource that uses the S0 pricing tier This option allows you to use the necessary built-in skills for OCR and text analytics and can handle larger workloads, which would be necessary for processing a large number of documents. The S0 pricing tier is a standard tier that provides a balance between cost and capabilities.

D - free tier is limited to 10,000 documents https://learn.microsoft.com/en-us/azure/search/search-limits-quotas-capacity#indexer-limits