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Microsoft

DP-100 · Question #551

You manage an Azure AI Foundry project. You plan to develop a RAG solution from a set of PDF files. To achieve this, you plan to create a vector index from the data. You need to select the location…

The correct answer is A. Azure Blob Storage B. Data in Azure AI Foundry. Azure AI Foundry vector indexes for RAG solutions support Azure Blob Storage and data already registered within Azure AI Foundry as input data sources.

Design and prepare a machine learning solution

Question

You manage an Azure AI Foundry project. You plan to develop a RAG solution from a set of PDF files. To achieve this, you plan to create a vector index from the data. You need to select the location of the data you plan to index. Which two data sources can you use? Each correct answer presents a complete solution. (Choose two.) NOTE: Each correct selection is worth one point.

Options

  • AAzure Blob Storage
  • BData in Azure AI Foundry
  • COneLake in Microsoft Fabric
  • DAzure Data Lake Storage Gen2

How the community answered

(51 responses)
  • A
    73% (37)
  • C
    18% (9)
  • D
    10% (5)

Why each option

Azure AI Foundry vector indexes for RAG solutions support Azure Blob Storage and data already registered within Azure AI Foundry as input data sources.

AAzure Blob StorageCorrect

Azure Blob Storage is a natively supported data source for vector index creation in Azure AI Foundry, enabling PDF and document files stored in blob containers to be chunked, embedded, and indexed directly.

BData in Azure AI FoundryCorrect

Data assets uploaded and registered within Azure AI Foundry can be selected directly as a data source when building a vector index, without requiring an external storage connection.

COneLake in Microsoft Fabric

OneLake in Microsoft Fabric is not a supported input data source for vector index creation in the Azure AI Foundry vector index workflow.

DAzure Data Lake Storage Gen2

Azure Data Lake Storage Gen2 is not listed as a supported data source for the Azure AI Foundry vector index creation wizard or SDK flow.

Concept tested: Azure AI Foundry vector index supported data sources for RAG

Source: https://learn.microsoft.com/en-us/azure/ai-studio/how-to/index-add

Topics

#RAG#Vector Indexing#Azure AI Foundry#Data Storage

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