- A
Add more indexers to the cluster to increase the speed of data model acceleration.
Why wrong: Indexers handle indexing, not acceleration; acceleration uses search peers.
- B
Limit the data model to only the most recent 7 days of data to reduce summary size.
Why wrong: Acceleration works best when the data model covers the entire time range needed.
- C
Create a separate acceleration summary for each search using the |accelerate command.
Why wrong: Acceleration is configured on the data model, not per search.
- D
Enable acceleration on the data model and schedule a periodic summary rebuild.
Acceleration precomputes summaries, and scheduling rebuilds ensures timeliness.
SPLK-1002 Data Models and Best Practices Practice Question
This SPLK-1002 practice question tests your understanding of data models and best practices. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A new Splunk admin wants to reduce the time it takes to run reports on a large dataset. They have enabled acceleration on a data model. Which of the following is a best practice to maximize acceleration benefits?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"best"Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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
Enable acceleration on the data model and schedule a periodic summary rebuild.
Option D is correct because enabling acceleration on a data model and scheduling a periodic summary rebuild ensures that the acceleration summaries are kept up-to-date without manual intervention. This maximizes the benefit of acceleration by pre-computing aggregations for the data model's root search, allowing reports to run against the smaller, optimized summary rather than the raw dataset, which significantly reduces query time.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add more indexers to the cluster to increase the speed of data model acceleration.
Why it's wrong here
Indexers handle indexing, not acceleration; acceleration uses search peers.
- ✗
Limit the data model to only the most recent 7 days of data to reduce summary size.
Why it's wrong here
Acceleration works best when the data model covers the entire time range needed.
- ✗
Create a separate acceleration summary for each search using the |accelerate command.
Why it's wrong here
Acceleration is configured on the data model, not per search.
- ✓
Enable acceleration on the data model and schedule a periodic summary rebuild.
Why this is correct
Acceleration precomputes summaries, and scheduling rebuilds ensures timeliness.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Splunk often tests the misconception that acceleration requires manual per-search commands or that scaling infrastructure alone solves performance issues, but the correct approach is to leverage Splunk's built-in data model acceleration with a scheduled rebuild to automate summary maintenance.
Detailed technical explanation
How to think about this question
Data model acceleration works by running the data model's root search periodically (based on the acceleration schedule) and storing the results in a summary index (e.g., 'dmc_summary'). When a report uses the accelerated data model, Splunk's search optimizer automatically rewrites the query to read from the summary instead of scanning raw events, which can reduce query times from minutes to seconds. The summary rebuild schedule (e.g., every hour or daily) ensures that new data is incorporated, and the acceleration time range (e.g., 'All time' or 'Last 7 days') controls how much data is summarized, balancing storage and performance.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the SPLK-1002 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Data Models and Best Practices — study guide chapter
Learn the concepts, then practise the questions
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FAQ
Questions learners often ask
What does this SPLK-1002 question test?
Data Models and Best Practices — This question tests Data Models and Best Practices — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable acceleration on the data model and schedule a periodic summary rebuild. — Option D is correct because enabling acceleration on a data model and scheduling a periodic summary rebuild ensures that the acceleration summaries are kept up-to-date without manual intervention. This maximizes the benefit of acceleration by pre-computing aggregations for the data model's root search, allowing reports to run against the smaller, optimized summary rather than the raw dataset, which significantly reduces query time.
What should I do if I get this SPLK-1002 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jun 30, 2026
This SPLK-1002 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-1002 exam.
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