Chapter 3 of 7 · Databricks Data Engineer Associate
Data Transformation and Modeling
Bronze to silver cleaning, joins, aggregation, Spark tuning, Gold objects and data quality.
- 3topics
- 16 minfast track
- 1diagrams and exhibits
- 22%of the exam
Topics in this chapter
Take them in order, or jump to the one you need.
- 1Cleaning and Reshaping Data from Bronze to SilverDatabricks DEA bronze to silver cleaning: handle nulls, cast types, add, drop, rename and split columns, filter rows and explode…5 min
- 2Joins, Deduplication, Aggregation and Spark TuningDatabricks DEA joins and unions, broadcast joins, dropDuplicates, count, approx_count_distinct, mean and summary, plus the basic…5 min
- 3Gold Layer Objects and Data QualityDatabricks DEA Gold layer: views vs materialized views vs streaming tables vs tables in Unity Catalog, expectations, CHECK…Diagram6 min
About this chapter
What this chapter covers
Data Transformation and Modeling is 22% of the Databricks Data Engineer Associate exam, the largest chapter. It covers what happens after data lands: cleaning bronze data into silver tables, reshaping and combining DataFrames, and building the Gold objects that BI and analytics teams query.
The chapter has three parts: cleaning and reshaping data with PySpark and SQL, joins, deduplication, aggregation and basic Spark tuning, and Gold layer objects with data quality rules.
Questions are mostly short scenarios in which the stated requirement (latency, cost, governance, data volume) decides the answer. They are single-answer multiple choice, and short SQL or PySpark is shown as text. There are no exhibits.
How the topics fit together
Bronze holds data as it arrived. Cleaning fixes nulls and types and reshapes columns into a silver table. Joins, deduplication and aggregation then produce the business view, which is published as a Gold object, with quality rules guarding each step.
- Cleaning questions ask which function handles nulls, types, renames, splits or arrays.
- Combine questions ask which join or union gives the stated result and when to broadcast.
- Tuning questions ask which Spark setting changes shuffle size, broadcast behavior or memory.
- Gold questions ask whether a view, materialized view, streaming table or table fits, and how an expectation treats bad rows.
Read the requirement word that decides the answer. "Always current, no storage" points to a view; "precomputed and fast for dashboards" points to a materialized view; "append only, process each new row once" points to a streaming table.
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.
Ready for more practice?
The full Databricks Data Engineer Associate question bank has 598 questions, with timed practice exams and an explanation for every answer.
This study guide is independent and is not affiliated with, endorsed by, or sponsored by Databricks. Vendor names, certification names and exam codes are trademarks of their respective owners and are used for identification only.