7.2 Statistical Table Reports
Key Takeaways
- Statistical table reports display transforming-command results as rows and columns on the Statistics tab and as Visualization type Table.
- Commands such as stats, top, and rare naturally produce tabular result sets that save cleanly as table reports.
- Choose Table when exact values, multiple metrics, or sortable comparisons matter more than shape or trend imagery.
- Save As Report after confirming Statistics looks correct so the table formatting and search travel together.
- Table reports are ideal dashboard panels for ops triage where readers need precise counts, percentages, or ranked lists.
7.2 Statistical Table Reports
Objective 6.3 asks you to create reports that display statistics (tables). On the User exam, this means recognizing when your search results are a statistical table, choosing the Table visualization when appropriate, and saving that view as a report teammates can reopen.
Tables are not “less advanced” than charts—they are the right answer when precision beats pictures.
What a Statistical Table Report Is
A statistical table report shows aggregated or ranked results as columns and rows—counts, averages, percentages, top values—rather than as a pie slice or line series. In Search you usually build it on the Statistics tab after a transforming command. On the Visualization tab, set the visualization type to Table when you want the same grid presentation saved with the report.
| View | What you see | When it matters |
|---|---|---|
| Events | Individual matching events | Exploration before transforming |
| Statistics | Tabular output of transforming commands | Primary place tables are born |
| Visualization → Table | Same stats rendered as a table viz | Confirms what the saved report will show as a table |
Typical producers of table-ready results
| Command pattern | Example result shape | Good table report use |
|---|---|---|
stats aggregations | count, avg, sum by split-by fields | KPI grids, multi-metric summaries |
top | field values with count and percent | Ranked “most common” lists |
rare | least common values with counts/percents | Outlier categories |
table / fields after transforms | Selected columns only | Clean ops handoff tables |
sort on stats output | Ordered rows | Leaderboards and triage queues |
You already practiced top, rare, and stats in Domain 5.0. Domain 6.3 is about packaging those results as reports that display as tables.
Building a Table Report Step by Step
- Bound the search with index, sourcetype, field filters, and time range.
- Transform with
stats,top, orrare(or a short pipeline that ends in a clear table). - Inspect the Statistics tab—column names and values should answer the business question.
- Optionally open Visualization, choose Table, and tidy column formatting if needed.
- Save As Report, name it clearly, set Private or App permissions.
Worked example: stats table
index=web sourcetype=access_combined
| stats count as requests, avg(bytes) as avg_bytes by status
| sort - requests
Statistics might look like:
| status | requests | avg_bytes |
|---|---|---|
| 200 | 18420 | 1520.4 |
| 404 | 932 | 410.2 |
| 500 | 118 | 880.0 |
Save as HTTP Status Request Volumes. Visualization type Table keeps the exact numbers front and center—ideal when on-call staff must compare 404 vs 500 counts without interpreting a chart.
Worked example: top as a table
index=security sourcetype=linux_secure action=failed
| top limit=10 user
top returns columns such as user, count, and percent. That is already a statistical table. Saving it as a report titled Top Failed Login Users creates a reusable ranked table for security review.
Worked example: rare as a table
index=web sourcetype=access_combined
| rare limit=10 uri_path
Rare paths are often more useful as a table than as a pie chart (tiny slices are hard to read). A report named Least Common URI Paths preserves that ranked scarcity view.
When Table Beats Chart
| Prefer a table when… | Prefer a chart when… | |---|---|---| | Readers need exact values | Readers need shape/trend at a glance | | Many columns/metrics appear together | One or two series tell the story | | Ranking and percent columns matter | Part-to-whole or time trends dominate | | Sorting/scanning rows is the workflow | Stakeholder slide-style visuals matter |
Exam scenarios often describe “show counts and percentages for each category” or “list the top 10 values with count and percent.” Those phrases point to statistical table reports, not pie aesthetics.
Formatting and Clarity Tips (User Level)
- Use meaningful column names via
as(count as failures) so the saved table is self-explanatory. - Limit columns with
fieldsortableafter transforms when extra fields clutter the grid. - Sort intentionally (
sort - count) so the first rows answer the question. - Keep titles specific: include the metric and the split (
Errors by Host, notStats1). - Descriptions should state the time intent (“Last 24 hours failed logins by user”).
You do not need advanced CSS, Simple XML <format> deep-dives, or Dashboard Studio table cells for this objective. Stay with Search → Statistics/Table → Save As Report.
Saving Table Reports for Dashboards
Table reports are excellent dashboard panels because they:
- Show precise numbers for ops and audit readers
- Match the Statistics output people already trust from Search
- Avoid misleading chart encodings when categories are numerous
In section 7.4 you will add such a report to a dashboard as a panel. For 6.3, the tested skill is creating the report that displays statistics as a table in the first place.
Exam Traps for 6.3
| Trap | Reality |
|---|---|
| Believing only charts can be saved as reports | Tables are first-class report visualizations |
| Saving from Events view and expecting a stats grid | Transform first; Statistics is where tables appear |
| Using a pie chart for a 25-column KPI grid | Table is the clearer statistical display |
Thinking top results are “not tables” | top/rare/stats outputs are tabular |
| Dragging CIM data models into the answer | User table reports come from search transforms |
Mini Scenario Drill
Your manager wants a reusable view of the ten most common
statuscodes with counts and percentages for the web index over the last 24 hours.
Strong approach:
index=web sourcetype=access_combined
| top limit=10 status
Confirm Statistics → Save As Report → Visualization Table (if not already) → name Top 10 HTTP Status Codes → share to App when ready.
That workflow is objective 6.3 in one pass: transforming results, table display, saved report.
Which search result is the best candidate for a statistical table report?
You need exact counts and percents for the top 10 users with failed logins. Which visualization type best matches a statistical table report?
Which command family most directly produces the Statistics-tab tables used in objective 6.3 reports?