Episode 7 — 1.1 Map Data Structures: Structured Tables, JSON, and Unstructured Content
This episode builds a clear mental model of data structures and why structure determines what analysis is feasible, efficient, and trustworthy on Data+ DA0-002. You will distinguish structured data, where columns and types are predictable, from semi-structured data such as JSON, where fields can vary and nesting is common, and from unstructured content such as free text, images, audio, and video, where meaning exists but must be extracted. The exam relevance shows up when a scenario asks what storage, transformation, or tooling approach fits the data you actually have, not the data you wish you had. You will learn to describe structure in plain terms and to identify the minimum steps required to make the data usable for a specific question.
You will work through practical examples that mirror how questions present messy reality: a customer profile that arrives as a table in one system, JSON event payloads in another, and support notes as raw text. You will compare extraction approaches for JSON, strategies for turning unstructured text into analyzable fields, and the risks of forcing structure too early and losing context. You will also cover validation habits that protect integrity, such as sampling, counting, and verifying that transformations preserve meaning. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
