Tableau-Desktop-Found Connecting to and Preparing Data Practice Question
When creating an extract, what is the impact of choosing 'Aggregate data for visible dimensions'?
⚠ Common exam trap
Candidates mistakenly believe aggregating extracts keeps all row-level detail intact, confusing summary aggregation with complete data preservation.
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
✓
It summarizes the data to reduce extract size.
This option reduces the size of the extract by summarizing data at the level of the dimensions currently in the view. This is an excellent optimization strategy for very large datasets where row-level granularity is not required for the dashboard. By storing only the necessary aggregates, the extract becomes much faster to query and takes up significantly less disk space, improving the overall efficiency of the analytical application.
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 keeps all original rows in the extract.
Why it's wrong here
Selecting this option does the opposite; it summarizes the data based on the visible dimensions, which physically removes the underlying row-level records. This significantly reduces the size of the extract but means that you lose the ability to drill down to individual records later.
- ✓
It summarizes the data to reduce extract size.
Why this is correct
By aggregating data based on the visible dimensions, Tableau creates a much smaller, pre-summarized dataset. This is highly effective for improving dashboard performance, especially when the goal is high-level reporting where individual row-level transaction detail is not required for the specific visualization being built.
- ✗
It only affects the metadata, not the physical data.
Why it's wrong here
This operation affects the actual physical data stored in the extract file, not just the metadata. Because it performs a physical aggregation of the underlying data points, it permanently changes the dataset's grain, which is why users must be careful when choosing this specific optimization option.
- ✗
It removes all measures from the extract.
Why it's wrong here
This option does not remove measures; it aggregates them based on the dimensions that are present. The measures are still included in the final extract, just in a pre-summarized format that aligns with the dimensions, ensuring that the necessary analytical data is still available for visualization.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Tableau (Salesforce) exam blueprint
This Tableau-Desktop-Found practice question is part of Courseiva's free Tableau (Salesforce) 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 Tableau-Desktop-Found exam.