Tableau-Desktop-Found Connecting to and Preparing Data Practice Question
You are connecting to a large SQL Server database and notice that performance is sluggish when dragging measures onto the canvas. You need to improve performance while still maintaining access to all historical data. Which action should you take?
⚠ Common exam trap
Candidates mistakenly choose to filter out historical data to improve speed, losing valuable context instead of leveraging extracts.
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
✓
Change the connection from Live to Extract.
Switching from a live connection to an extract improves performance by pulling data into Tableau's high-performance Hyper engine. This local, compressed snapshot reduces query latency against the source database. This is a foundational practice for optimizing large datasets where real-time updates are not strictly required, allowing analysts to interact with dashboards without waiting for long network round-trips to the SQL Server.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Filter the data source to include only the current year.
Why it's wrong here
Filtering at the source reduces the total volume, but it removes historical data from the dashboard entirely. If the requirement is to maintain access to all data while improving interaction speeds, this approach fails because users can no longer perform year-over-year analysis using the original full dataset.
- ✓
Change the connection from Live to Extract.
Why this is correct
Extracts utilize the Hyper data engine, which is highly optimized for analytical queries. By localizing the data, you eliminate network overhead and database query latency. This is the standard method for improving interactivity in Tableau Desktop without sacrificing the integrity or availability of the full historical data set.
- ✗
Enable 'Assume Referential Integrity' in the Data Source tab.
Why it's wrong here
Assume Referential Integrity can improve query performance by allowing Tableau to perform joins more efficiently; however, it does not address the fundamental bottleneck of a live connection. If the database remains live, network latency and high query volume will still result in poor performance for end users.
- ✗
Convert all dimensions to measures.
Why it's wrong here
Changing data roles does not change how Tableau queries the underlying data source. Measures perform aggregations, while dimensions provide context. Converting them does not reduce the number of rows or the complexity of the SQL queries generated, so it will have no meaningful impact on dashboard performance.
About these practice questions
One of 126 original Tableau-Desktop-Found practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. 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.