Data preparation is the cleaning, reshaping, and combining of raw data before analysis or reporting. It can include removing duplicates, fixing formats, joining sources, filtering bad records, and standardizing fields so downstream tools can trust the output.
In cyber security, data preparation matters because many breaches and reporting errors start with messy input and manual handling. Copy-paste workflows, ad hoc exports, and untracked transformation steps can leak sensitive data, introduce mistakes, or hide tampering. Attackers may target preparation pipelines to poison analytics, alter reports, or exploit weak validation in scripts and spreadsheets. Defenders reduce risk by using repeatable workflows, input validation, access controls, audit logs, and versioned transformations. Good data preparation makes results reproducible, traceable, and harder to manipulate.