DP-900 Describe an analytics workload on Azure Practice Question
Which TWO Azure services can be used to store semi-structured data? (Choose two.)
⚠ Common exam trap
A common mix-up: candidates confuse 'semi-structured data' with 'unstructured data' and incorrectly assume only NoSQL databases qualify, forgetting that Azure Blob Storage can store semi-structured files like JSON or XML as blobs, even though it is not a 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
✓
Azure Cosmos DB
Azure Cosmos DB is a NoSQL database service that natively supports semi-structured data through its flexible schema model. It allows storing JSON documents, key-value pairs, and graph data without requiring a fixed schema, making it ideal for semi-structured data like user profiles, IoT telemetry, or product catalogs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Azure Cosmos DB
Why this is correct
Azure Cosmos DB is a multi-model NoSQL database service that stores documents natively in JSON. Rather than imposing a fixed relational schema, it allows each item to have a different shape, with properties mapped to indexes automatically. This makes it a first-class store for semi-structured data such as sensor telemetry, IoT events, or any payload that evolves over time.
- ✓
Azure Blob Storage
Why this is correct
Azure Blob Storage is an object storage service that stores unstructured files as blobs, but it also handles semi-structured data when the file itself is semi-structured. You can upload JSON, Parquet, or Avro files directly, and applications can read the file with schema-on-read logic. Because Blob Storage does not parse or index the contents, it acts as a durable and scalable data lake for semi-structured datasets.
- ✗
Azure SQL Database
Why it's wrong here
Azure SQL Database is a relational database engine that structures data into tables, rows, and columns with enforced schemas and constraints. While T-SQL includes functions like OPENJSON and the JSON data type can hold text, JSON is not a first-class table storage format here. Highly variable or nested semi-structured data is difficult to model efficiently, so Azure SQL Database is not the recommended choice.
- ✗
Azure Synapse Analytics
Why it's wrong here
Azure Synapse Analytics is a distributed analytics and data warehousing service built around relational tables and columnar storage for structured data. Dedicated SQL pools require a defined schema before loading, and while serverless SQL can use OPENROWSET to query Parquet or JSON files in Azure Storage, those files are stored in Blob or Data Lake, not inside Synapse itself. Therefore it is a query and analytics engine for semi-structured files, not a storage service for them.
- ✗
Power BI
Why it's wrong here
Power BI is a business intelligence and visualization platform that creates dashboards and reports from data stored elsewhere. It can import data into an in-memory cache or issue DirectQuery live queries, but it is not a data store such as a database or object storage. You would create reports in Power BI, not persist semi-structured records with it, so it does not qualify as an Azure storage service.
Go deeper
Related to this question
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Data Roles and Core Concepts
Key term
Structured data
Structured data is information that is organized in a predefined format, typically in rows and columns, making it easy to search, process, and analyze by computers.
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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