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Describe an analytics workload on AzuremediumMultiple ChoiceObjective-mapped

DP-900 Describe an analytics workload on Azure Practice Question

A company wants to analyze customer feedback from surveys and social media. The data includes both structured (ratings) and unstructured (comments) text. They plan to use Azure Cognitive Services for sentiment analysis. Which service should they use for text analytics?

⚠ Common exam trap

Many candidates confuse Azure Synapse Analytics or Azure Machine Learning as general-purpose analytics tools, overlooking that Azure AI Language is the dedicated, pre-built service for text analytics tasks like sentiment analysis.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Azure AI Language

Azure AI Language (formerly part of Azure Cognitive Services) provides pre-built text analytics capabilities, including sentiment analysis, key phrase extraction, and language detection. This service is specifically designed to process unstructured text data like survey comments and social media posts, making it the correct choice for analyzing customer feedback.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Azure Synapse Analytics

    Why it's wrong here

    Azure Synapse Analytics is a cloud-scale data warehousing and big data analytics service, not a text-analytics API. It can ingest and query survey data using T-SQL or Spark, but it lacks any pre-built sentiment analysis capability. To derive sentiment from feedback you would need to call an external AI service like Azure AI Language or build a custom model, making it the wrong choice for this straightforward requirement.

  • Azure Cosmos DB

    Why it's wrong here

    Azure Cosmos DB is a globally distributed multi-model NoSQL database designed for high-throughput, low-latency data storage, not for understanding natural language. While you can store survey feedback as JSON documents in Cosmos DB, it provides no built-in sentiment analysis or text analytics features. Sentiment scoring would require integrating a separate service, so Cosmos DB alone cannot fulfill the requirement.

  • Azure AI Language

    Why this is correct

    Azure AI Language is the correct choice because it offers a pre-built, API-accessible sentiment analysis capability specifically for text. You can send survey responses to its endpoint and receive document-level and sentence-level sentiment scores, along with confidence scores, without training any models. As part of Azure Cognitive Services, this service is purpose-built for exactly this kind of customer feedback analysis.

  • Azure Machine Learning

    Why it's wrong here

    Azure Machine Learning is a comprehensive platform for building, training, and deploying custom machine learning models, not a pre-built service for sentiment analysis. Using it would require you to label a dataset, engineer text features, train a model, and manage its lifecycle—work that is unnecessary when a ready-made solution exists. For simple survey feedback sentiment, Azure AI Language is far more appropriate.

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This DP-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-900 exam.