Free sections from Ultra Transcenders DP-750: Implementing Data Engineering Solutions Using Azure Databricks, on the comparisons and decisions the exam keeps asking about.
What standard (formerly shared) and dedicated (formerly single user) access modes allow, and when each is required.
Who manages the files, what DROP TABLE does to each, and why Databricks recommends managed tables.
How SQL UDF row filters and column masks restrict data per user, and how they differ from dynamic views.
How the two retention properties and VACUUM decide which table versions you can still query or restore.
SCD types 0, 1, 2 and others compared, and when to keep history in a dimension table.
The table-size thresholds for partitioning, partition sizing, and why liquid clustering is usually the better choice.
How expectations validate records in Lakeflow Spark Declarative Pipelines and what each violation action does.
Job and task notifications, system destinations, duration warnings and how retries affect which alerts are sent.