DP-900 - Describe Core Data Concepts (30% of the exam) - Section 1.1

Describe ways to represent data including structured, semi-structured, and unstructured formats.

Distinguish structured data (fixed schema, rows and columns), semi-structured data (flexible tags such as JSON and XML), and unstructured data (free text, images, video). Recognise that schema on write enforces structure at load time, while schema on read defers interpretation to query time.

structured datasemi-structured dataunstructured dataJSON XMLschema on read vs write

Practice question for this objective

Free sampleDescribe Core Data Conceptseasy

Which of the following is an example of unstructured data?

AA relational table linking orders to customers by key values.
BA JSON document whose fields differ from one record to the next.
CA spreadsheet of rows and columns with consistent headers.
DA collection of audio and video files with no fixed schema. Correct

Audio, video, documents and images are unstructured data because they carry no fixed or partial schema. Unstructured data is data that is not structured or semi-structured, and the grounding lists audio and video files among its examples.

Why A is wrong: Tempting because it is a clear data example, but tables related by key values are structured data following a fixed tabular schema.

Why B is wrong: Tempting as JSON looks free-form, but JSON with varying fields is the common format for semi-structured data, not unstructured data.

Why C is wrong: Tempting because spreadsheets feel informal, but rows and columns with consistent headers form a fixed schema, making this structured data.

Why D is correct: Correct. Unstructured data is data that is not structured or semi-structured, and the grounding lists audio and video files among its examples.

See more DP-900 practice questions, answers explained.

Exam traps in Describe Core Data Concepts

Answers that look right on this material and are not. Each one is a distractor from a different question in the DP-900 bank for this domain.

Apache Parquet columnar format
Why it is wrong: Parquet is an optimized binary columnar format, not human-readable text.
Comma-separated values (CSV)
Why it is wrong: CSV is flat delimited text with fields split by commas, so it cannot natively nest objects inside collections the way a hierarchical document does.
An attribute of the entity being stored
Why it is wrong: Attributes are represented by columns in a tabular schema, not by rows.

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