SECAI Core · phase 3 of 15
Data processing
The set of steps used to collect, clean, transform, and organize raw data into a structured, usable form
The Explain card
- Plain English
- Data processing is the sequence of steps that takes raw data and collects, cleans, transforms and organises it into a structured form a model can actually use.
- Example
- Before training a log anomaly detector, a pipeline parses raw syslog, normalises timestamps, masks IP addresses, and converts everything to numeric features.
- Why it matters
- Every processing step is a place where data can be altered, dropped or injected. Attackers who reach the pipeline can poison training data without ever touching the model.
- Hook
- Raw in, model-ready out, and every step in between is an attack surface.
Where it sits in the deck
Phase 3: Data Fundamentals: Types, Pipelines, and Preparation
Models are only as good as their data — understand the raw material and the engineering that shapes it before covering how it flows or breaks.
