Splunk Core Certified User Practice Exam 2025 - Free Splunk Core Certified User Practice Questions and Study Guide

The Instant Pivot data model is created by utilizing the search criteria entered during the initial search. This process allows Splunk to automatically generate a data model based on the fields and data types that are relevant to the user's specific search query. By using the search criteria, Splunk can contextualize the data within the existing datasets and present a visual representation that helps users to understand and explore their data efficiently.

When a user inputs a search query, Instant Pivot analyzes that input and extracts the necessary information, which it converts into a visual format suitable for analysis. This dynamic creation of the data model enables users to quickly create pivots and gain insights without extensive manual configuration.

The other options do not accurately describe how Instant Pivot constructs its data model. Manually defining fields involves a more hands-on approach that is not inherently characteristic of Instant Pivot's automated capabilities. Utilizing predefined templates suggests a static approach, which doesn't align with the flexibility and responsiveness of Instant Pivot. Merging multiple data sources does play a role in data processing but is not the fundamental mechanism through which Instant Pivot creates its data model based on a single search query.