Question 1

In the medallion architecture, which layer holds cleaned, filtered and conformed data ready for analysis?

Accepted Answer

Silver Bronze is raw ingested data, silver is cleaned and conformed, and gold is curated business-level aggregates. Analysts most often build on silver and gold.

Question 2

Which Databricks SQL object is designed to display query results and can be refreshed on a schedule for stakeholders?

Accepted Answer

A dashboard Databricks SQL dashboards present query visualisations and can refresh on a schedule, making them the standard way to share analytics with stakeholders.

Question 3

In Unity Catalog, what is the correct object hierarchy from top to bottom?

Accepted Answer

Metastore → Catalog → Schema → Table Unity Catalog organises data as Metastore → Catalog → Schema (database) → Table/View. Knowing this three-level namespace is a common exam point.

Question 4

An analyst notices a Delta table accumulating many tiny files from frequent small writes, hurting read performance. Which command compacts them into larger files?

Accepted Answer

OPTIMIZE OPTIMIZE compacts many small files into fewer, larger ones, improving read efficiency. VACUUM removes obsolete files, and ANALYZE TABLE just collects statistics — neither compacts files.

Question 5

Which statement about a Databricks SQL refresh schedule is incorrect?

Accepted Answer

A query on a refresh schedule does not use a SQL Warehouse A scheduled refresh must run the query on an active SQL Warehouse, so claiming it uses none is false. The refresh interval range, the distinction from alerts, and Query Editor configuration are all correct.

Question 6

Which approach lets you ingest data directly from cloud-based object storage in Databricks?

Accepted Answer

Create an external table specifying the object storage path with LOCATION An external table that references the object storage path via LOCATION reads data directly from cloud storage without copying it — the DBFS/FROM and PATH variants use the wrong clause.

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