DP-900 Describe core data concepts Practice Question
A healthcare application stores patient vital signs readings. Each reading is a JSON document with fields: PatientID, Timestamp, HeartRate, BloodPressure (systolic and diastolic). The application frequently queries for all readings of a specific patient within a time range, and the schema varies occasionally (e.g., new optional fields are added). How should this data be classified?
⚠ Common exam trap
Many exam-takers confuse 'structured' with 'having fields'—they see PatientID and Timestamp and assume it must be structured, but the key differentiator is schema flexibility (optional fields, varying structure) which defines semi-structured data.
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
✓
Semi-structured
The data is semi-structured because it is stored as JSON documents, which have a flexible schema that can vary between records (e.g., new optional fields can be added). JSON documents are self-describing and do not require a fixed schema like relational tables, but they still have organizational properties (fields like PatientID, Timestamp) that distinguish them from unstructured data like plain text or images. The application's queries on specific fields (PatientID, Timestamp) further confirm the data has structure, but the schema flexibility rules out structured or relational classifications.
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
Why it's wrong here
Structured data is organized into a strict, predefined schema such as relational tables with fixed columns and data types. Patient vital signs readings are typically key-value pairs or JSON-like records where fields (e.g., heart rate, temperature, blood pressure) can vary per record, making a rigid tabular format awkward and requiring extensive normalization or nullable columns to accommodate variability.
- ✓
Semi-structured
Why this is correct
Semi-structured data, such as JSON, XML, or key-value pairs, uses tags or markers to separate elements and permits schema flexibility. Vital signs readings naturally fit this model because each reading can include a variable set of measured parameters (e.g., some include SpO2, some include respiratory rate) without requiring every record to have identical fields, and the order of fields does not matter.
- ✗
Unstructured
Why it's wrong here
Unstructured data lacks a predefined data model or structure, including free-form text, images, audio, and video. Patient vital signs readings are inherently organized into discrete data elements (like timestamps and numeric measurements) with identifiable labels, so they cannot be considered unstructured; they have enough inherent structure to be parsed and queried automatically.
- ✗
Relational
Why it's wrong here
Relational data is a specific form of structured data stored in tables with fixed schemas, primary keys, and foreign keys enforcing relationships. Vital signs readings are often collected as event streams or JSON documents from IoT devices, which do not conform to a fixed relational schema and require flexible schemas to accommodate new sensor types, so relational storage would be too rigid and require costly schema migrations.
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
Key term
Schema
A schema is a blueprint or logical structure that defines how data is organized, stored, and accessed in a database or information system.
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