Databricks Data Intelligence Platform

What this chapter covers

Understanding of Databricks Data Intelligence Platform (Lakehouse Platform) is 11% of the Databricks Data Analyst Associate exam. It covers the map every other chapter assumes: what each platform component does, how Unity Catalog organizes data, and where Marketplace fits.

The chapter has three parts: the core components (Databricks SQL, Unity Catalog, Delta Lake, Lakeflow, Mosaic AI, Lakebase and the Data Intelligence Engine), the objects you see in Catalog Explorer, and the role of Databricks Marketplace.

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

Data arrives through Lakeflow or Marketplace, lands as Delta Lake tables, and is governed by Unity Catalog. Analysts query it with Databricks SQL on a SQL warehouse and share results through AI/BI dashboards and Genie Agents.

• Component questions describe a need and ask which platform part meets it.
• Catalog Explorer questions ask about the three level namespace, managed vs external tables, views and lineage.
• Semantic questions ask what certified tables and metric views add for consistent reporting.
• Marketplace questions ask what can be obtained there and how it appears in your workspace.

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.