DA0-002 Visualization and Reporting Practice Question
In Tableau, an analyst wants to create a calculated field that returns the average sales per customer only for customers who have made more than five purchases. Which Tableau function or approach would be most efficient?
⚠ Common exam trap
The trap is reaching for table calculations or context filters when the requirement is a per-entity aggregate filter, which only LOD expressions handle correctly in Tableau.
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
✓
Use a Level of Detail expression to count purchases per customer, then filter
A Level of Detail (LOD) expression such as {FIXED [Customer] : COUNT([Order ID])} computes the purchase count per customer independently of the view's granularity, which can then be used in a filter or conditional calculation. This is the canonical Tableau approach for row-level filtering based on aggregated per-entity metrics. It is efficient because it pushes the aggregation to the data source level.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a table calculation for running sum
Why it's wrong here
A running sum table calculation accumulates values along a partition and cannot restrict rows to customers exceeding five purchases. The requirement needs a fixed level-of-detail count per customer used as a filter condition. Running sums suit cumulative trend visualisations, not per-customer qualification.
- ✗
Use a context filter on the number of records
Why it's wrong here
A context filter on record count filters underlying rows before other filters, but cannot evaluate a per-customer purchase threshold and then average sales across those customers. The requirement needs a fixed level-of-detail calculation counting purchases per customer. Context filters suit reducing query scope or top-N dimension filtering.
- ✓
Use a Level of Detail expression to count purchases per customer, then filter
Why this is correct
A Level of Detail expression computes the purchase count at customer granularity, independent of the view's dimensions, so filtering on that fixed aggregate correctly restricts results to customers exceeding five purchases. This satisfies the per-customer threshold constraint without altering the underlying data source.
- ✗
Create a parameter to filter customers
Why it's wrong here
Parameters supply user-driven values and cannot themselves aggregate or filter rows by purchase count within a calculated field. The requirement needs a level-of-detail expression or fixed aggregate to count purchases per customer. Parameters would be correct for letting users switch dimensions or thresholds interactively.
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Last reviewed September 2026 · checked against the official CompTIA exam blueprint
This DA0-002 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DA0-002 exam.