DP-900 Describe core data concepts Practice Question
A logistics company collects sensor data from delivery trucks. Each sensor sends a JSON message that includes a fixed set of core fields (truck ID, timestamp) but also includes optional fields such as temperature, humidity, and engine diagnostics depending on the sensor type. The JSON structure varies between messages. How should this data be classified?
⚠ Common exam trap
The trap here is that candidates often mistake any data with a consistent core set of fields as 'structured data', overlooking that the presence of optional, varying fields makes it semi-structured.
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 data
The JSON messages contain a fixed set of core fields (truck ID, timestamp) but also include optional fields that vary per message, meaning the data has a flexible schema. This mixture of structured fields and variable attributes is the defining characteristic of semi-structured data, which does not require a rigid schema like a relational table but still has organizational properties (e.g., key-value pairs). In Azure, this type of data is commonly stored in services like Azure Cosmos DB or Azure Blob Storage with JSON format.
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 requires a predefined, fixed schema where every record has the same attributes and data types, typically managed in relational tables with rows and columns. The sensor data from the trucks is delivered as JSON payloads that can contain different fields for different readings, so it does not conform to a uniform table structure. Because the schema is not rigid and fields vary between records, the data cannot be classified as structured.
- ✓
Semi-structured data
Why this is correct
Semi-structured data does not enforce a strict schema but uses tags, keys, or markers to give the data some organizational structure. In this scenario, the truck sensor data arrives as JSON, where each document has name-value pairs but the presence and combination of fields can vary, making it self-describing. These properties—some structure, but no rigid tabular schema—are exactly what define semi-structured data, so this is the correct classification.
- ✗
Unstructured data
Why it's wrong here
Unstructured data has no inherent structure or semantic markup, such as free-form text, images, or audio, and typically requires machine learning or similar techniques to extract meaning. JSON, even with optional fields, always contains key-value pairs, separators, and nesting rules that make the data parseable and queryable. Since the truck sensor data has embedded organizational properties, it does not qualify as unstructured.
- ✗
Relational data
Why it's wrong here
Relational data is a strict subset of structured data that is stored in tables made up of rows and columns, with a fixed schema and enforced relationships (primary and foreign keys). The JSON sensor feeds from the trucks would require a heavy transformation process to be normalized into such tables, and even then important flexibility would be lost. Because the data as collected is not represented as relations, calling it relational would be inaccurate.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
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.
Key term
Semi-structured data
Semi-structured data is information that has some organizational tags or markers but does not fit into a strict table format like a spreadsheet row and column.
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