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DP-900 Describe core data concepts Practice Question

A research team needs to store thousands of PDF reports that vary in length and structure. The storage solution must allow flexible schema and support access from multiple programming languages via HTTP. Which data storage category best describes these reports?

⚠ Common exam trap

A common mix-up: candidates confuse 'semi-structured' with 'unstructured' because PDFs can contain text and metadata, but the exam expects you to recognize that the file itself is a binary blob with no schema enforced by the storage system.

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

Unstructured data

C is correct because PDF reports with varying length and structure are binary files that do not conform to a predefined data model or schema, which is the definition of unstructured data. Azure Blob Storage or Amazon S3 are typical services for storing such unstructured data, accessed via HTTP REST APIs from any programming language.

Answer analysis

Option-by-option breakdown

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

  • Structured data

    Why it's wrong here

    Structured data is organized into rows and columns with a fixed, predefined schema—such as a relational table with explicit data types and constraints—that allows direct querying with SQL. PDF reports, however, are binary files that combine text, fonts, images, and layout metadata; they have no such tabular structure or enforced schema. Applying structured data categories to PDFs is incorrect because the documents cannot be meaningfully queried or aggregated without first extracting content.

  • Semi-structured data

    Why it's wrong here

    Semi-structured data (e.g., JSON, XML, or key-value pairs) has self-describing properties like tags, keys, or nested objects that provide a flexible, machine-readable organization. While a PDF may contain internal metadata (author, title, timestamps), the main body is not encoded in a standardized, schema-bearing format; its text is rendered visually, not exposed through tags or fields. Therefore, PDFs fail the defining criteria of semi-structured data, which requires some discoverable organizational structure.

  • Unstructured data

    Why this is correct

    Unstructured data has no predefined data model or schema, and PDFs are a classic example because their content—text, images, tables, and annotations—is stored in a way that cannot be directly queried without dedicated extraction. Azure Blob Storage is designed to store such binary files as blobs and is a common, cost-effective choice for large volumes of PDF reports. 'Unstructured' does not mean the files lack content; it means they lack a predictable, database-friendly structure that a query engine can exploit automatically.

  • Transactional data

    Why it's wrong here

    Transactional data refers to records of discrete events (e.g., an order, a payment, a log entry) captured in an online transaction processing (OLTP) system, with supporting attributes like timestamps, customer IDs, and amounts. PDF reports are static documents that persist information rather than record discrete operational events, and they are stored as files rather than as rows in a transaction log or database table. Classifying them as transactional data confuses the document's storage format with the type of business activity described in the content.

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-term compliance archive

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