Splunk SPLK-1002 Exam Dumps

Get All Splunk Core Certified Power User Exam Questions with Validated Answers

SPLK-1002 Pack
Vendor: Splunk
Exam Code: SPLK-1002
Exam Name: Splunk Core Certified Power User
Exam Questions: 297
Last Updated: January 6, 2026
Related Certifications: Splunk Core Certified Power User
Exam Tags: Intermediate Level Data AnalystsSecurity Analysts
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Free Splunk SPLK-1002 Exam Actual Questions

Question No. 1

A data model consists of which three types of datasets?

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Correct Answer: B

The building block of adata model. Each data model is composed of one or more data model datasets. Each dataset within a data model defines a subset of the dataset represented by the data model as a whole.

Data model datasets have a hierarchical relationship with each other, meaning they have parent-child relationships. Data models can contain multiple dataset hierarchies. There are three types of dataset hierarchies: event, search, and transaction.

https://docs.splunk.com/Splexicon:Datamodeldataset


Question No. 2

Which delimiters can the Field Extractor (FX) detect? (select all that apply)

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Correct Answer: B, C, D

The Field Extractor (FX) is a tool that helps you extract fields from your data using delimiters or regular expressions. Delimiters are characters or strings that separate fields in your data. The FX can detect some common delimiters automatically, such as pipes (|), spaces ( ), commas (,), semicolons (;), etc. The FX cannot detect tabs (\t) as delimiters automatically, but you can specify them manually in the FX interface.

Question No. 4

Which field will be used to populate the field if the productName and product:d fields have values for a given event?

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Correct Answer: B

The correct answer is B. The value for the productName field because it appears first.

The coalesce function is an eval function that takes an arbitrary number of arguments and returns the first value that is not null. A null value means that the field has no value at all, while an empty value means that the field has a value, but it is '''' or zero-length1.

The coalesce function can be used to combine fields that have different names but represent the same data, such as IP address or user name. The coalesce function can also be used to rename fields for clarity or convenience2.

The syntax for the coalesce function is:

coalesce(<field1>,<field2>,...)

The coalesce function will return the value of the first field that is not null in the argument list. If all fields are null, the coalesce function will return null.

For example, if you have a set of events where the IP address is extracted to either clientip or ipaddress, you can use the coalesce function to define a new field called ip, that takes the value of either clientip or ipaddress, depending on which is not null:

| eval ip=coalesce(clientip,ipaddress)

In your example, you have a set of events where the product name is extracted to either productName or productid, and you use the coalesce function to define a new field called productINFO, that takes the value of either productName or productid, depending on which is not null:

| eval productINFO=coalesce(productName,productid)

If both productName and productid fields have values for a given event, the coalesce function will return the value of the productName field because it appears first in the argument list. The productid field will be ignored by the coalesce function.

Therefore, the value for the productName field will be used to populate the productINFO field if both fields have values for a given event.


Search Command> Coalesce

USAGE OF SPLUNK EVAL FUNCTION : COALESCE

Question No. 5

Which of the following file formats can be extracted using a delimiter field extraction?

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Correct Answer: A

A delimiter field extraction is a method of extracting fields from data that uses a character or a string to separate fields in each event. A delimiter field extraction can be performed by using the Field Extractor (FX) tool or by editing the props.conf file. A delimiter field extraction can be applied to any file format that uses a delimiter to separate fields, such as CSV, TSV, PSV, etc. A CSV file is a comma-separated values file that uses commas as delimiters. Therefore, a CSV file can be extracted using a delimiter field extraction.


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