Tableau-Desktop-Found Connecting to and Preparing Data Practice Question
Which TWO of the following are valid ways to combine data from different sources in Tableau?
⚠ Common exam trap
Candidates often include 'Data Extract' or 'Data Source' as a way to combine data, confusing the storage format with the actual methodology used to associate data from multiple sources.
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
✓
Blending
Understanding how to integrate data is fundamental to Tableau. Blending and Relationships are the primary methods for combining data from multiple sources. Choosing the right one depends on the nature of the data, the desired level of granularity, and performance requirements. Relationships are generally preferred for their flexibility and intelligence, while blending serves as a useful secondary tool for quick, high-level analysis when more complex modeling is not feasible.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Blending
Why this is correct
Blending is a method to query two different data sources separately and then aggregate the results at the visualization level. It is useful for sources that cannot be joined or related, or when data is at different granularities and you need to perform quick, ad-hoc comparisons without heavy modeling.
- ✗
Data Mining
Why it's wrong here
Data mining refers to the process of discovering patterns in large data sets. It is not a feature in Tableau for combining data sources. While you can perform data analysis, 'Data Mining' is a broad industry term and not a specific functional mechanism for connecting and integrating datasets.
- ✓
Relationships
Why this is correct
Relationships are the recommended, modern method for linking tables. They are flexible, context-aware, and avoid the duplication issues associated with traditional joins. They allow for a logical model that automatically adjusts aggregation levels depending on the fields included in the visualization, making them superior to older techniques.
- ✗
Data Sorting
Why it's wrong here
Sorting is a visualization technique used to order data in a view. It has nothing to do with combining multiple data sources or integrating datasets. It is an operation performed on existing data, not a method for managing data connections or creating a combined data source model.
- ✗
Extracting
Why it's wrong here
Extracting is the process of creating a local copy of data to improve performance. It is a format, not a method for combining disparate data sources. While you can extract combined data, extracting itself does not provide the logic to merge or relate data from two different sources.
About these practice questions
Courseiva writes every Tableau-Desktop-Found question from scratch — 126 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
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.