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Server-Certified-Associate Tableau Server Certified Associate

  • Tableau
  • 5 free sample questions

About this exam

Server-Certified-Associate is the Tableau exam Tableau Server Certified Associate. Paid practice material for this exam is not available yet, but you can try its free sample questions.

Exam code
Server-Certified-Associate
Vendor
Tableau
Practice questions
Not available yet
Free sample questions
5
Question bank last updated
Not available yet

Try 2 sample questions

Taken from the free sample set for Server-Certified-Associate.

Question 1

Interpret the following command:
tsm maintenance backup -f ts-sample_backup -d -sr monthly -st 01:00 -sd 15 -sn monthly-backup


  1. Option A:
    Creates a backup schedule that runs on the 15th of each month at 1am
  2. Option B:
    Creates a backup schedule that runs every 15 minutes starting at 1am each day
Show answer and explanation

Correct answer: A

The command tsm maintenance backup -f ts-sample_backup -d -sr monthly -st 01:00 -sd 15 -sn monthly-backup is used in Tableau Services Manager (TSM) to create a scheduled backup. The parameter -sr monthly specifies that the schedule repeats monthly, -st 01:00 sets the start time to 1:00 AM, and -sd 15 indicates that the backup should run on the 15th day of the month. The schedule is named monthly-backup using -sn monthly-backup. Therefore, this command creates a backup schedule that executes on the 15th of every month at 1:00 AM, making Option A correct.

Question 2

Which of the following statements accurately describe how the Data Engine process consumes
memory and CPU?

  1. Option A:
    The Data Engine is designed to leverage all available CPU and memory on the machine to
    provide the fastest response times

  2. Option B:
    The Data Engine is designed to conserve all available CPU and memory on the machine to
    provide efficient but fast response times
Show answer and explanation

Correct answer: A

The Tableau Data Engine (Hyper) is designed to fully utilize available system resources such as CPU and memory in order to deliver fast query performance and low-latency analytics. Rather than conserving resources, it is optimized for performance and will take advantage of multiple cores and available memory to process data efficiently and quickly. This design allows it to handle large datasets and complex queries with high speed.
See all 5 free sample questions