Tableau-Desktop-Found Understanding Tableau Concepts Practice Question
A logistics analyst combines shipment records from two tables in a single data source. The Shipments table contains one row per shipment, and the Packages table contains one row per package, with many packages belonging to a single shipment. The analyst relates the two tables on Shipment ID and then builds a view of Total Freight Cost by Carrier. The freight cost column lives only in the Shipments table. Which statement describes what happens to the freight cost values in the resulting view?
⚠ Common exam trap
The trap here is assuming that relating tables with different granularities automatically duplicates the higher-level measure, which is the behaviour of a physical join rather than a relationship.
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
✓
Freight cost values are preserved because the relationship aggregates shipment-level measures at the shipment level of detail, independent of the package rows.
Relationships keep related tables logically separate and let Tableau determine the level of detail required by the view. Shipment-level measures such as freight cost are aggregated at the shipment grain, so adding package rows does not multiply them. Physical joins, by contrast, can repeat rows and inflate totals.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Freight cost values are preserved because the relationship aggregates shipment-level measures at the shipment level of detail, independent of the package rows.
Why this is correct
Relationships establish a logical association between tables, and Tableau queries each table at the level of detail needed for the view. Measures from the Shipments table are aggregated at the shipment grain, so adding package-level dimensions does not multiply shipment freight costs unless a package-level dimension is also used, in which case the values are allocated appropriately across that finer grain.
- ✗
Freight cost is summed across all packages in the shipment, producing a value equal to the shipment cost multiplied by the package count.
Why it's wrong here
That multiplication behaviour describes a physical join that repeats the shipment row for each package, which is the classic fan-out problem. Relationships avoid this by keeping the tables logically separate and aggregating each at its own level of detail. The analyst would only see inflated totals if the tables were physically joined and the shipment-level measure were then summed across the duplicated rows.
- ✗
The relationship fails to resolve because the two tables are at different levels of detail, so freight cost returns null for every carrier.
Why it's wrong here
Differing levels of detail between related tables is a normal and supported case. Tableau resolves the association logically and determines the correct grain at query time, so shipment-level measures remain available even when package rows are present. Returning nulls would only occur if the join keys did not match or if the relationship were misconfigured, neither of which is described here.
- ✗
Freight cost is duplicated for each matching package row, so the totals are inflated unless the analyst switches to a many-to-many relationship.
Why it's wrong here
Tableau relationships are designed to avoid this duplication at the level of detail of the view. The aggregation is computed at the level of the dimension used in the view, so shipment-level values are not multiplied by the number of packages. Switching to a many-to-many relationship would not correct a duplication problem because the relationship already handles the differing granularity appropriately.
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Last reviewed September 2026 · checked against the official Tableau (Salesforce) exam blueprint
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