Managing Data

What this chapter covers

Managing Data is 8% of the Databricks Data Analyst Associate exam. It covers how an analyst finds trusted data in Unity Catalog, labels it, traces where it came from, and cleans it before reporting.

The chapter has three parts: discovering and using certified datasets, tagging assets with governed tags and reading lineage in Catalog Explorer (including external lineage), and cleaning Unity Catalog tables in SQL by removing invalid rows and handling missing values.

Questions are mostly short scenarios in which the stated requirement (freshness, cost, who may see what, audience) decides the answer. They are single-answer multiple choice, and short SQL is shown as text. There are no exhibits.

How the topics fit together

You start by finding the right table, ideally one marked certified. Tags and lineage tell you what the data contains and where it came from. Cleaning in SQL then removes bad rows and fills gaps so reports are correct.

• Discovery questions ask how to find trusted tables and what the certified mark means.
• Tag questions ask how governed tags differ from ordinary tags and who may apply them.
• Lineage questions ask what the lineage graph shows and how systems outside Databricks are added.
• Cleaning questions show short SQL and ask which statement removes, replaces or keeps rows.

How to use these pages

Each topic page has the same shape, so you can skim for what you need.

• What it is: the idea in plain words.
• How it works: the mechanism, with tables and examples.
• What to remember for the exam: the facts to memorize and how questions are phrased.
• Common mistakes: the classic traps.
• Check yourself: three questions to test your understanding.