FC0-U71 Data and Database Fundamentals Practice Question
A startup is choosing a data store for a product catalog where each item may have a different set of attributes, such as a camera with lens mount and sensor size versus a book with ISBN and page count. The catalog is read far more often than it is written, and the schema is expected to change frequently. Which TWO characteristics make a document-oriented NoSQL store a suitable fit? (Choose two.)
⚠ Common exam trap
The trap here is assuming a flexible data store must also provide the same referential integrity guarantees as a relational database, when those are separate properties.
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
✓
Each item can be stored as a self-contained document whose fields vary from item to item
Variable per-item attributes and frequent schema change are the two driving requirements. A document store satisfies both because each item carries its own fields and new fields can be introduced incrementally rather than through a global migration. Fixed column layouts and cross-table integrity guarantees describe relational behavior instead.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
It enforces a fixed column layout that all catalog items must follow
Why it's wrong here
A rigid, uniform column layout is the hallmark of a tabular relational design, not a flexible document store. Imposing one fixed set of columns on cameras, books, and other unrelated items would leave many columns empty or force awkward workarounds, which is the opposite of what this catalog scenario needs.
- ✓
Each item can be stored as a self-contained document whose fields vary from item to item
Why this is correct
A document store keeps each catalog item as a single record with its own set of named fields, so a camera record and a book record can coexist without forcing every item to share one rigid column layout. This directly matches the requirement that items carry different attributes and that the shape of records can evolve.
- ✗
It guarantees strict multi-table referential integrity across all catalog records
Why it's wrong here
Enforcing that every foreign key value matches an existing primary key in another table is a relational guarantee. Document stores do not generally enforce cross-collection referential rules of that kind, and the scenario does not ask for them; the need is flexible per-item attributes, not cross-table constraints.
- ✗
It requires every query to join at least three collections before returning a result
Why it's wrong here
Joining several collections for every read is neither a requirement nor a desirable property. A document store typically returns a whole item from one collection read, which suits a read-heavy catalog. Mandating multi-collection joins would add complexity and latency without helping the variable-attribute requirement.
- ✓
The schema can evolve by adding or removing fields in documents without a planned migration of every existing record
Why this is correct
Because fields are written per document, a new attribute can be introduced for new items while older items simply lack that field. This supports the stated expectation that the catalog schema changes frequently, since adding an attribute does not require rewriting the entire collection before the change can be used.
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Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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