Study Databricks DE-ASSOC Data Processing: key concepts, common traps, and exam decision cues.
This is the heaviest technical center of DE-ASSOC. Questions here are usually not just about writing code. They test whether you can explain why a pipeline is shaped a certain way, how data should move from raw to curated layers, and which transformation or runtime behavior fits the scenario.
| Lesson | Focus |
|---|---|
| 3.1 Medallion | Learn why bronze, silver, and gold are different stages of responsibility rather than cosmetic folder names. |
| 3.2 Lakeflow | Learn why Lakeflow pipeline definitions simplify repeatable ETL compared with hand-wired notebook chains. |
| 3.3 SQL & DataFrames | Learn the SQL and PySpark operations the exam uses to test safe table changes and aggregation logic. |
| 3.4 Transform Performance | Learn how workload type and query behavior drive cluster and runtime decisions. |
| If the question is really about… | Go first to… |
|---|---|
| bronze, silver, gold, and why data belongs in one layer instead of another | 3.1 Medallion Architecture and Layer Purpose |
| declarative ETL structure, managed dependencies, or pipeline definition | 3.2 Lakeflow Declarative Pipelines and ETL Design |
| SQL verbs, merges, inserts, creates, groupBy, or PySpark aggregations | 3.3 DDL, DML, DataFrames & Aggregation Patterns |
| shuffle-heavy jobs, runtime tuning, or choosing cluster shape for a transformation workload | 3.4 Cluster Configuration and Transformation Performance |