Data Model Acceleration (DMA)in Splunk is used to improve search performance by creating summarized, indexed versions of data models that enable much faster retrieval than querying raw indexed data directly. This acceleration is particularly beneficial for complex searches, dashboards, and reports based on large datasets.
DMA precomputes and stores data aggregates, allowing near real-time responses for repeated queries.
It does not normalize data—that function is handled by CIM and data models themselves.
DMA is unrelated to comparing algorithms or modeling response actions.
According toSplunk documentation, enabling acceleration on data models significantly reduces search latency and enhances user experience, especially in security operations with high volumes of data.
[Reference:, Splunk Docs: Data Model Acceleration, Splunk Cybersecurity Defense Analyst Study Guide, Chapter 4: Search Optimization, Splunk Enterprise Security Performance Guide, , ]
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