SPLK-1004 Data Models And CIM Practice Test 2 — 15 Questions

Question 1

A Splunk administrator is designing a new data model to support Pivot and tstats searches. The administrator wants to ensure that the data model can be accelerated efficiently and that users can drill down to raw events from Pivot. Which two configurations are required to achieve these goals? (Choose two.)

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Define at least one event-based dataset with a constraint that references indexed fields.. To accelerate a data model and enable efficient Pivot drill-down, the model must include at least one event-based dataset with a constraint that filters events, and acceleration must be enabled with a summary range. These two configurations ensure that summary files are built and that tstats can query them quickly. Other elements like transactions or lookups are optional and not required for the core functionality.

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Add a lookup to enrich the data model with additional fields.

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Create a transaction object that groups related events by a common field.

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Define a root event dataset and at least one child dataset to enable hierarchical Pivot.

Question 2

A Splunk administrator notices that a data model acceleration summary is taking much longer than expected to build, and the search head is experiencing performance degradation. Which configuration change should be made to mitigate this issue without sacrificing data model functionality?

Accepted Answer

Adjust the acceleration schedule to run during off-peak hours.. Data model acceleration can consume significant search head resources. Scheduling it during off-peak hours reduces contention with user searches, improving performance without changing the acceleration coverage or functionality. This is a best practice for managing acceleration load.

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Reduce the acceleration time range by adjusting the `max_time` setting.

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Increase the number of search heads in the cluster.

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Enable `summariesonly` for all tstats searches to reduce load.

Question 3

A Splunk power user is creating a new data model and wants to ensure that it is compatible with the Common Information Model (CIM). Which of the following is a required step to make a data model CIM-compliant?

Accepted Answer

Map the data model's fields to the corresponding CIM data model fields using the data model editor.. CIM compliance requires that a data model uses the exact field names and object hierarchy defined in the CIM. This is accomplished by mapping your data model's fields to the CIM fields, typically using eval expressions or field aliases within the data model editor. Tags or acceleration do not ensure compliance, and the CIM Validator only identifies issues, it does not fix them. Proper mapping is the essential step.

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Run the CIM Validator tool to automatically convert the data model to be CIM-compliant.

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Add the data model to the list of accelerated data models in the CIM app's configuration.

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Ensure that the data model is tagged with the 'cim' tag in the data model settings.

Question 4

A Splunk administrator notices that a data model's acceleration is taking longer than expected and the summary files are larger than anticipated. The data model includes several event-based datasets with constraints that filter on fields like sourcetype and index. Which action would most effectively reduce the acceleration time and summary size without losing necessary data?

Accepted Answer

Add more constraints to each event-based dataset to further filter events.. Adding more constraints to event-based datasets is the most effective way to reduce acceleration time and summary size. Constraints filter events at search time, so only relevant events are included in the acceleration summaries. This reduces the data volume processed during acceleration and stored in summaries. Other options either increase data volume or disable acceleration, which is not desirable. Careful constraint design ensures that necessary data is retained while optimizing performance.

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Disable acceleration on some datasets and rely on raw searches for those.

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Change the data model's acceleration to use a smaller bucket size.

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Increase the summary range to cover a longer period.

Question 5

A Splunk user is working with the CIM and needs to ensure that events from a custom application are properly categorized under the Authentication data model. The events contain a field named 'auth_result' with values 'success' and 'failure'. What is the correct way to map this field to the CIM-compliant field?

Accepted Answer

Use the CIM mapping wizard in Splunk Web to map auth_result to action and apply the authentication tag.. The CIM mapping wizard provides a guided way to map custom fields to CIM fields and apply the necessary tags. For the Authentication data model, events must be tagged with 'authentication' and the 'action' field must contain values like 'success' or 'failure'. The wizard handles both field mapping and tagging, ensuring full CIM compliance. Other methods like field aliases or calculated fields may partially work but do not cover the tagging requirement, which is essential for the data model to recognize the events.

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Use a field alias to map auth_result to action.

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Create a calculated field using eval to set action = auth_result.

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Modify the data model JSON to add a new field named action with a regex extraction.

Question 6

A Splunk power user is designing a data model for authentication events. They want to ensure that the data model supports the CIM Authentication data model. Which two actions must they take to make the data model CIM-compliant for authentication? (Choose two.)

Accepted Answer

Tag the relevant events with the 'authentication' event type.. To make a data model CIM-compliant for authentication, you must tag events with the 'authentication' event type and map fields to the CIM field names. These steps ensure that the data model aligns with the CIM standards and can be used with CIM-based searches. Acceleration, index creation, and adding to the CIM app are not required for compliance.

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Add the data model to the CIM app's list of data models.

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Enable acceleration on the data model to improve performance.

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Create a new index specifically for authentication events.

Question 7

Which CIM data model should be used to normalize authentication data?

Accepted Answer

Authentication. The Authentication data model in the Common Information Model (CIM) is specifically designed to normalize authentication data, including successful and failed logins, account changes, and privilege escalations. It provides a standardized set of fields and tags for authentication events across different sources.

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Change Analysis

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Network Traffic

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Email

Question 8

A user reports that a data model acceleration summary is 'incomplete'. What is the most likely cause?

Accepted Answer

The summary search has not completed its initial scan of the historical data. A data model acceleration summary is marked 'incomplete' when the summary search has not yet completed its initial scan of all historical data. Data model acceleration builds summaries over time; until the initial backfill finishes, the summary is incomplete. Permissions, lookups, or disk size are not direct causes of this status.

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The user does not have 'admin' permissions

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The root search uses a lookup

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The model is too large for the disk

Question 9

You want to extend a data model object to include new fields. Which object type allows you to add child objects that inherit base constraints?

Accepted Answer

Child object. A child object in a data model is the object type specifically designed to inherit constraints from a parent (base) object and add new fields or constraints. Child objects extend the base event or search object, inheriting its constraints while allowing additional field definitions. This is the mechanism Splunk provides for building hierarchical data models without duplicating base constraints.

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Lookup object

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Event object

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Pivot object

Question 10

What is the primary benefit of using a Data Model over standard raw search results in Pivot?

Accepted Answer

They provide faster performance for large datasets. Data models, especially when accelerated, pre-compute and store summarized results in high-performance tsidx files, so Pivot queries run dramatically faster than ad-hoc raw searches over large datasets. This performance gain is the primary reason to use a data model in Pivot.

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They allow for raw log access only

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They are always real-time

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They provide better data security

Question 11

When configuring a CIM-compliant data model, what happens if a field is tagged but the event type is not associated with the model?

Accepted Answer

The data will not appear in the data model. For an event to be included in a CIM-compliant data model, it must be matched by an event type that is explicitly associated with the data model's root or child objects. Tagging a field alone does not create that association; the event type must be added to the data model's constraints. Without the event type linkage, the events are simply not selected by the data model's search, so they will not appear in the model.

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The model will use default values

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The model will trigger a warning

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The search will automatically include all indexed events

Question 12

You are creating a new data model and need to define a root object that includes only events where the field 'status' is '200'. Which feature should be used to restrict this data?

Accepted Answer

Data model root search. The data model root search defines the base search that constrains which events are included in the data model. By specifying a search like 'status=200' in the root event's search clause, only events matching that condition become part of the dataset. This is the correct place to restrict data at the root level.

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Pivot filter

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Accelerate command

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CIM mapping

Question 13

When using Pivot, what determines the field labels shown to the user?

Accepted Answer

The data model field display names. In Pivot, the field labels displayed to the user are determined by the data model field display names. These are defined in the data model's JSON configuration, allowing administrators to provide user-friendly names (e.g., 'Client IP' instead of 'clientip'). Raw log field names, user preferences, and index names do not control the labels shown in Pivot.

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The raw log field names

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The user's preference settings

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The index name

Question 14

If a data model is accelerated, where are the summary files stored on the indexer?

Accepted Answer

In the _datamodel_summary index. When a data model is accelerated, Splunk stores the summary files in the _datamodel_summary index. This is a dedicated internal index created specifically for data model acceleration summaries, separate from the main index and other internal indexes. Knowing this location is important for capacity planning and troubleshooting.

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In the main index

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In the user's home directory

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In the /var/lib/splunk/storage directory

Question 15

When an accelerated data model object is updated, what happens to the existing summary files?

Accepted Answer

They are rebuilt to match the new definition. When an accelerated data model object is updated — for example, changing a field, constraint, or calculation — Splunk invalidates the existing summary files and rebuilds them to reflect the new definition. The acceleration process re-runs the underlying search across the relevant time range and writes fresh TSIDX summary files. This ensures that reports using the data model return results consistent with the updated schema.

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They remain unchanged until a reboot

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They are moved to a cold bucket

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They are deleted and never recreated