The correct answer is to decrease the acceleration time range in the data model definition. This works because data model acceleration pre-computes and stores summary data for a specified time range, so reducing that range directly cuts the disk space consumed by the summary on the indexers. Since the dashboard refreshes every 30 minutes, a shorter acceleration window—such as the last 7 days instead of 30—still keeps the most recent, frequently queried data instantly available, preserving dashboard performance while freeing up storage. On the SPLK-1002 exam, this question tests your understanding of how acceleration summaries impact indexer resources and the trade-off between disk usage and query speed. A common trap is to confuse acceleration time range with summary retention or to suggest deleting the entire data model, which would break the dashboard. Remember the memory tip: "Shorter range, same performance—trim the time, not the data."
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 Splunk administrator notices that a data model acceleration summary is consuming excessive disk space on the indexers. The data model is used for a dashboard that refreshes every 30 minutes. What is the best course of action to reduce disk usage while maintaining dashboard performance?
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 the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Decrease the acceleration time range in the data model definition.
Option B is correct because decreasing the acceleration time range in the data model definition directly reduces the amount of data the summary covers, which lowers disk usage on the indexers. Since the dashboard refreshes every 30 minutes, a shorter acceleration range (e.g., last 7 days instead of 30) still keeps the most recent data pre-computed for fast queries, maintaining performance for the refresh interval.
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.
✗
Disable data model acceleration and rely on raw data searches.
Why it's wrong here
Disabling acceleration would degrade dashboard performance.
✓
Decrease the acceleration time range in the data model definition.
Why this is correct
Reducing the acceleration time range reduces the amount of stored summary data, saving disk space.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Decrease the backfill time for the data model.
Why it's wrong here
Backfill time controls how far back to initially populate summaries, not ongoing storage.
✗
Increase the acceleration time range to speed up summary generation.
Why it's wrong here
Increasing time range would store more summaries, increasing disk usage.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is confusing the acceleration time range (which controls the scope of pre-computed data) with the backfill time (which only affects the initial historical build), leading candidates to incorrectly choose option C.
Detailed technical explanation
How to think about this question
Data model acceleration in Splunk uses a summary index that stores pre-computed results for a specified time range (e.g., last 7 days). The acceleration time range is set in the data model definition via the `acceleration.earliest_time` property, and the summary is rebuilt periodically based on the `acceleration.refresh_interval`. Reducing this range limits the number of buckets the summary covers, directly reducing the number of TSIDX files and bloom filters stored on indexers, which is the primary driver of disk consumption.
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.
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: Decrease the acceleration time range in the data model definition. — Option B is correct because decreasing the acceleration time range in the data model definition directly reduces the amount of data the summary covers, which lowers disk usage on the indexers. Since the dashboard refreshes every 30 minutes, a shorter acceleration range (e.g., last 7 days instead of 30) still keeps the most recent data pre-computed for fast queries, maintaining performance for the refresh interval.
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
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A user reports that a data model acceleration is consuming excessive disk space on the indexer. The data model has a summary range of 90 days. Which action is best to reduce disk space usage while maintaining acceptable query performance?
easy
A.Increase the acceleration frequency to rebuild summaries more often.
✓ B.Reduce the summary range to 30 days.
C.Disable acceleration for the data model.
D.Delete old indexed data that is not frequently queried.
Why B: Reducing the summary range from 90 days to 30 days directly decreases the amount of data that the acceleration precomputes and stores on the indexer. This minimizes disk space consumption while still accelerating queries for the most recent, commonly accessed data. Maintaining a shorter summary range ensures acceptable performance for recent queries without the overhead of storing summaries for older, less frequently accessed time periods.
Last reviewed: Jun 11, 2026
Question Discussion
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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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