DEA-C02 Data Transformation Practice Question
A data engineer is designing a transformation pipeline that uses Snowpark to process data. The pipeline must perform complex data cleaning and feature engineering. Which TWO capabilities of Snowpark are specifically designed to support these transformations? (Choose two.)
⚠ Common exam trap
A common mix-up: candidates confuse general benefits like processing data in-place or ML libraries with the specific transformation capabilities of Snowpark, namely the DataFrame API and UDFs.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The ability to execute user-defined functions (UDFs) written in Python, Java, or Scala within Snowflake.
Snowpark's DataFrame API allows developers to write transformations in Python, Java, or Scala, providing a familiar and expressive way to perform complex data cleaning and feature engineering. Additionally, Snowpark supports UDFs in these languages, enabling custom logic to be executed within Snowflake. These two capabilities directly empower the development of sophisticated transformation pipelines.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The ability to execute user-defined functions (UDFs) written in Python, Java, or Scala within Snowflake.
Why this is correct
Snowpark supports UDFs that can be written in Python, Java, or Scala and executed within Snowflake. This allows custom transformation logic to be applied to data at scale, which is essential for complex feature engineering and data cleaning tasks that go beyond built-in SQL functions.
- ✗
The ability to automatically materialize transformation results into a new table without explicit DDL.
Why it's wrong here
Snowpark does not automatically materialize results into tables; you must explicitly write the DataFrame to a table using the write method. While it simplifies data persistence, it does not eliminate the need for DDL or explicit write operations. This is not a specific capability for transformations.
- ✗
The ability to execute transformations on data without moving it out of Snowflake's storage layer.
Why it's wrong here
While Snowpark processes data within Snowflake, this is a general benefit, not a specific capability for transformations. The question asks for capabilities that support complex data cleaning and feature engineering, and this is more of an architectural advantage. It is not a distinct feature like the DataFrame API or UDFs.
- ✓
The ability to write transformations in Python, Java, or Scala using a DataFrame API similar to Apache Spark.
Why this is correct
Snowpark provides a DataFrame API in multiple languages, allowing developers to express transformations declaratively. This is a core capability that enables complex data cleaning and feature engineering by leveraging familiar programming constructs and libraries, and it integrates with Snowflake's processing engine.
- ✗
The ability to use the Snowpark ML library for building and deploying machine learning models directly in Snowflake.
Why it's wrong here
Snowpark ML is a library for machine learning, not specifically for data transformation. While it can be used in feature engineering, it is not a core transformation capability. The question asks for capabilities designed to support transformations, and Snowpark ML is more focused on ML workflows.
About these practice questions
One of 229 original DEA-C02 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Snowflake exam blueprint
This DEA-C02 practice question is part of Courseiva's free Snowflake certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C02 exam.