Normalization in the context of data analysis refers to the process of organizing data to reduce redundancy and improve efficiency in storing and sharing. By filtering, tagging, and queuing, Miley is effectively normalizing the data---converting it from various unstructured formats into a structured, more accessible format. This makes the data easier to analyze, store, and share. Normalization is crucial in cybersecurity and threat intelligence to manage the vast amounts of data collected and ensure that only relevant data is retained and analyzed. This technique contrasts with sandboxing, which is used for isolating and analyzing suspicious code; data visualization, which involves representing data graphically; and convenience sampling, which is a method of sampling where samples are taken from a group that is conveniently accessible. Reference:

'The Application of Data Normalization to Database Security,' International Journal of Computer Science Issues

SANS Institute Reading Room, 'Data Normalization Considerations in Cyber Threat Intelligence'