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AI Infrastructure and TechnologiesmediumMultiple ChoiceObjective-mapped

AI0-001 AI Infrastructure and Technologies Practice Question

A company needs to store large volumes of unstructured data (PDFs, images, logs) for future AI model training. The data must be easily accessible by data scientists using Spark and must support cost-effective storage. Which data infrastructure is MOST appropriate?

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

Amazon S3 data lake

A data lake stores raw, unstructured data at low cost and integrates with Spark. Data warehouses are for structured, processed data; vector databases are for embeddings.

Answer analysis

Option-by-option breakdown

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

  • Snowflake data warehouse

    Why it's wrong here

    Snowflake is optimized for structured, query-ready data; storing raw unstructured files would be expensive and inefficient.

  • Relational database like Amazon RDS

    Why it's wrong here

    Relational databases are designed for structured, transactional data; they are not suitable for storing large files.

  • Pinecone vector database

    Why it's wrong here

    Vector databases store embeddings for similarity search, not raw unstructured data files.

  • Amazon S3 data lake

    Why this is correct

    S3 is a scalable, low-cost object store for unstructured data; it integrates with Spark and is ideal for a data lake.

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