3.2 Deploy Data Modeling Rules for Data Normalization XSIAM-ENGINEER Practice Questions (Page 5)

Questions 21–25

1. 21foundation · medium

   What is a best practice for handling variations in raw log formats within a data modeling rule?

   • AManually correct the raw logs before they are ingested
   • BCreate a separate rule for every possible format variation
   • CUse multiple parsing steps or conditional logic to handle different formats
   • DIgnore logs that do not match the expected format
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2. 22foundation · medium

   Which technique is commonly used in data modeling rules to extract fields from raw log text?

   • ANetwork packet capture
   • BMachine learning classification
   • CSQL joins
   • DRegular expressions (regex)
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4. 23foundation · medium

   What is a key aspect of validating data modeling rules?

   • AEnsuring the normalized output matches the expected schema and values
   • BEnsuring the rule is approved by management
   • CEnsuring the rule is written in Python
   • DEnsuring the rule runs as fast as possible
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5. 24application · medium

   A company ingests logs from a custom application that uses a non-standard timestamp format. The security team wants to use XSIAM's built-in time-based correlation rules. What is the primary reason they need a data modeling rule for this log source?

   • ATo filter out irrelevant logs before they are stored.
   • BTo create a new dataset for the custom application.
   • CTo increase the storage efficiency of the log data.
   • DTo convert the custom timestamp into the standard timestamp field expected by XSIAM.
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6. 25application · medium

   A data modeling rule needs to map a country code (e.g., 'US', 'DE') to a full country name (e.g., 'United States', 'Germany'). Which technique should be used?

   • AUse an EDL (External Dynamic List) to map the code to the name.
   • BUse a transformation that concatenates the code with a static string.
   • CUse a regex to replace the code with the name.
   • DMap the code directly to the country name field.
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