Which component improves the performance of Splunk ES searches?

Data models are structured hierarchies used in Splunk that enable efficient searching and reporting on datasets within Splunk Enterprise Security (ES). By pre-defining relationships and accelerating certain types of searches, data models enhance search performance significantly.

When users conduct searches on data models, the system can leverage the optimized structure of the model to retrieve relevant data more quickly. This not only speeds up the search process but also improves overall performance because data models are designed to minimize the computational load required to process queries. Additionally, data models can be accelerated, meaning that Splunk can pre-compute results for specific queries, further reducing the time needed for search results to be returned.

The other options, while they may play a role in the overall operation and maintenance of a Splunk environment, do not directly improve search performance in the same way that data models do. Data retention policies manage how long data is stored but do not influence the speed of searches. Documenting processes provides clarity and guidance for users but does not impact system performance. Automated incident alerts can notify users about issues but do not enhance search query speed or efficiency.