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DP-900 Describe core data concepts Practice Question

A retail company collects data from online transactions including order ID, customer details, product IDs, quantities, and timestamps. The data is stored in a relational database and used for order processing and inventory management. Which characteristic of this data makes it structured?

⚠ Common exam trap

Many candidates confuse 'structured' with any organized storage format (like JSON or key-value pairs), but the DP-900 exam specifically defines structured data as having a fixed schema with rows and columns in a relational database.

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

It is stored in rows and columns with a predefined schema.

Structured data is defined by a fixed schema where each entity (e.g., orders) is stored in rows and columns with predefined data types (e.g., INT for order ID, VARCHAR for customer details). This relational model enforces consistency and enables efficient querying via SQL for order processing and inventory management.

Answer analysis

Option-by-option breakdown

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

  • It is stored in rows and columns with a predefined schema.

    Why this is correct

    Structured data is defined by a rigid, predefined schema, which means each record conforms to a specified set of columns with fixed data types. This tabular format—rows and columns—enables relational database features such as ACID transactions (atomicity, consistency, isolation, durability), primary/foreign key constraints, and efficient SQL querying. The schema is enforced at write time, so every inserted row matches the expected structure, making it the foundational model for transactional systems like online order processing.

  • It is stored as key-value pairs.

    Why it's wrong here

    Key-value pairs are a NoSQL data model where each item is an opaque key associated with a value, and there is no enforced structure or relationships between items. This model prioritizes high-speed lookups and horizontal scalability, but it does not support the fixed tabular organization, multi-column constraints, or ACID transactions that characterize structured data. Storing online transaction data as key-value pairs would sacrifice query flexibility and referential integrity, making it incorrect to describe this as structured data.

  • It is stored in JSON format with variable fields.

    Why it's wrong here

    JSON with variable fields is the hallmark of semi-structured data, not structured data. Each object can contain a different set of fields, meaning the schema is flexible and applied implicitly at read time rather than enforced at write time. While JSON has some organizational syntax—key-value pairs and nesting—it lacks the strict, predefined column layout and data-type consistency that define structured data. This flexibility is useful for evolving data shapes but is fundamentally different from the rigid relational model used for structured transactional data.

  • It is stored in unstructured text files.

    Why it's wrong here

    Unstructured text files, such as plain-text logs or free-form documents, have no predefined schema or organizational pattern, so their content cannot be directly queried by column or row. Unlike structured data, where every field occupies a predictable position and data type, unstructured data requires parsing, natural language processing, or other interpretation to extract meaning. Online transaction data—with clear attributes like product ID, quantity, and price—cannot be meaningfully stored in this format and still be treated as structured.

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