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After data is ingested, which data management step is essential to ensure raw data can be accelerated by a Data Model and used by ES?
Correct Answer: C
Explanation After data is ingested, the data management step that is essential to ensure raw data can be accelerated by a data model and used by ES is normalization to the Splunk Common Information Model (CIM). The CIM is a standard and consistent way of naming and structuring the fields and tags for different types of data, such as network, web, email, authentication, and malware. The CIM allows you to use the same search queries and dashboards across different data sources, even if they have different formats or schemas. Normalizing data to the CIM involves mapping the raw data fields and tags to the CIM fields and tags using technology add-ons. Technology add-ons are Splunk apps that provide the necessary configurations and extractions for specific data sources. By normalizing data to the CIM, you can enable data model acceleration for the data models that use the CIM fields and tags. Data model acceleration is a feature that speeds up searches and reports that use data models by pre-computing and storing the results of the data model queries. Data model acceleration is required for most of the dashboards and correlation searches in Splunk Enterprise Security. References = Data models in the Splunk Common Information Model Data model acceleration