SPLK-1001 Practice Question: Creating Reports, Dashboards and Visualizations
A compliance report must show the average latency per service for each hour over the past 30 days. The data set contains millions of events. To ensure the report finishes within a reasonable time, which approach is recommended?
⚠ Common exam trap
Splunk often tests the misconception that timechart or stats with span is sufficient for large datasets, but the trap here is that candidates overlook the performance advantage of tstats over a data model, which is specifically designed for high-speed aggregation on massive datasets.
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
✓
Use the tstats command over a data model
The tstats command is optimized for use with data models and runs on indexed fields in the tsidx files, making it far faster than stats or timechart on raw events for large datasets. By pre-defining a data model with the latency field and using tstats, you avoid scanning millions of raw events and instead query pre-aggregated statistics, ensuring the report completes within a reasonable time.
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 the tstats command over a data model
Why this is correct
tstats leverages acceleration and is optimized for large datasets.
- ✗
Use timechart span=1h avg(latency) by service
Why it's wrong here
This scans raw events and may be slow on large data volumes.
- ✗
Use stats avg(latency) by service, _time span=1h
Why it's wrong here
Similar to timechart, it processes raw data and can be slow.
- ✗
Pre-process data using a summary index that runs hourly
Why it's wrong here
While summary indexing helps, it requires ongoing maintenance and may not be as efficient as tstats for ad-hoc queries.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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