DP-900 Describe core data concepts Practice Question
A company stores customer names and addresses in a fixed-format file where each record has the same fields in the same order. This type of data is best described as:
⚠ Common exam trap
Many exam-takers confuse 'fixed-format' with 'semi-structured' because both can be stored in files, but the key distinction is that fixed-format enforces a rigid schema with identical fields per record, whereas semi-structured allows schema flexibility.
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
✓
Structured data
A fixed-format file where each record has the same fields in the same order is a classic example of structured data. Structured data conforms to a rigid schema, such as a table with defined columns and data types, making it easily searchable and processable by relational database systems like Azure SQL Database. The consistent field order and fixed format allow for direct parsing without interpretation.
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 this is correct
Structured data is organized into a predefined schema, meaning every record contains the same named fields in the same order, such as CustomerName and CustomerAddress. A fixed-format file enforces this rigid layout, often with fixed-width columns or delimiters, so each row maps cleanly to a relational table. This predictability makes it directly queryable with SQL and suitable for Azure SQL Database or Synapse Analytics.
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Semi-structured data
Why it's wrong here
Semi-structured data sits between structured and unstructured: it has tags, keys, or markers that provide some organization, but the schema is flexible and fields can vary from one entity to another. Examples like JSON, XML, and Parquet allow nested or optional attributes, whereas the customer file in the scenario has a fixed, uniform format. Since fixed-format data does not permit this schema variability, it is not semi-structured.
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Unstructured data
Why it's wrong here
Unstructured data has no predefined data model or field structure; it is raw content such as text documents, images, audio, and video that cannot be easily stored in rows and columns. The fixed-format customer file, by contrast, has explicit fields and a consistent layout for every record, which is the opposite of unstructured. Therefore, it must be classified as structured data rather than unstructured.
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Streaming data
Why it's wrong here
Streaming data describes how data is produced, such as continuous high-velocity events from sensors or clickstreams, not the structural format of the data itself. A fixed-format file containing customer names and addresses is static and batch-oriented; even if processed in near real time, the file's structure remains unchanged. Hence, streaming data is a data processing characteristic, not a valid classification for this fixed-format dataset.
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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
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.
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