Miley, an analyst, wants to reduce the amount of collected data and make the storing and sharing process easy. She uses filtering, tagging, and queuing technique to sort out the relevant and…

Question

Options

• ASandboxing
• BNormalization
• CData visualization
• DConvenience sampling

• A
  8% (4)
• B
  87% (45)
• C
  4% (2)
• D
  2% (1)

Explanation

Normalization (B) is correct because it describes the process of converting raw, unstructured data into a standardized, structured format - which is exactly what filtering (removing irrelevant data), tagging (categorizing it), and queuing (organizing its flow) accomplish together. The goal is a cleaner, smaller, and more shareable dataset.

Sandboxing (A) is an isolation technique used to run untrusted code or files in a contained environment to prevent system harm - it has nothing to do with structuring data. Data visualization (C) is about displaying data through charts and dashboards, not reducing or structuring it. Convenience sampling (D) is a statistical method of collecting data from the most accessible sources - it's a collection strategy, not a processing technique.

Memory tip: Think of normalization as making data "normal" - you filter the noise, tag what matters, and queue it into a consistent shape. In SIEM tools especially, normalization is the step that turns messy log data into something machines (and analysts) can actually use.

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