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SPLK-1001 Practice Question: A large enterprise has multiple Splunk indexers…

A large enterprise has multiple Splunk indexers and is using data model acceleration to speed up dashboards. The dashboards are slow despite acceleration being enabled. The data model has many root events and child datasets. Which best practice should the administrator consider to improve performance?

⚠ Common exam trap

Many exam-takers assume acceleration always improves performance, but they overlook that the acceleration process itself can become a bottleneck if the data model has too many root events, leading them to choose options that increase workload (like increasing summary range) rather than reducing it.

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

Reduce the number of root events in the data model.

Data model acceleration creates a summary of the data, but the acceleration process must traverse all root events to build the child datasets. If there are too many root events, the acceleration job itself becomes slow and resource-intensive, negating the performance benefit. Reducing the number of root events directly reduces the workload for acceleration, allowing the summaries to be built faster and queries to run against the accelerated data more efficiently.

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 tstats commands on the data model without acceleration.

    Why it's wrong here

    tstats requires acceleration to be effective; without it, performance is poor.

  • Reduce the number of root events in the data model.

    Why this is correct

    Fewer root events simplify the acceleration summary, improving build and search performance.

  • Replicate the data model on each indexer to distribute load.

    Why it's wrong here

    Replication duplicates effort and is not a standard best practice for acceleration.

  • Increase the summary range to cover more data.

    Why it's wrong here

    A larger summary range increases build time and may not improve query speed.

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This SPLK-1001 practice question is part of Courseiva's free Splunk 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 SPLK-1001 exam.