Data models are crucial for data normalization within the Common Information Model (CIM) framework. They define a standardized structure for how data should be organized and related in Splunk, representing various data types within a consistent schema. This standardization facilitates the compatibility of data from different sources, allowing analysts to perform searches and analysis without having to deal with differing formats and representations.
By utilizing data models, organizations can ensure that events from various sources are categorized consistently, enabling improved correlation, analysis, and visualization of security incidents. Data models provide a unified approach to how data is interpreted and queried in Splunk, supporting various analytic processes, including security monitoring and incident response. Therefore, data models play a foundational role in achieving effective data normalization within cybersecurity efforts using Splunk.