DEA-C02 Data Transformation Practice Question
Which feature allows a Data Engineer to define a transformation pipeline where the target table automatically updates when the source table changes, without needing to manually define a schedule?
⚠ Common exam trap
Test-takers often confuse Dynamic Tables with traditional Tasks or Streams, failing to recognize that Dynamic Tables automatically manage schedules and dependencies declaratively.
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
✓
Dynamic Tables
Dynamic Tables provide a declarative approach to data engineering. By defining the target table based on a SQL query, Snowflake manages the dependency graph and incrementally updates the data. This abstracts away the complexity of managing tasks, streams, and manual refresh schedules, making it the most modern and efficient way to handle continuous data transformation in a pipeline.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Tasks with Streams
Why it's wrong here
While Tasks and Streams can create an automated pipeline, they are imperative, not declarative. The engineer must manually define the task graph, dependencies, and refresh logic. Dynamic Tables improve upon this by allowing the engineer to specify the result, while the system handles the underlying execution.
- ✓
Dynamic Tables
Why this is correct
Dynamic Tables are designed for declarative pipelines. You define the transformation query, and Snowflake automates the materialization and incremental updates. This eliminates the need for manual scheduling or monitoring of complex task chains, greatly simplifying the data engineering workflow for continuous transformation tasks.
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Materialized Views
Why it's wrong here
Materialized Views are restricted in their transformation capabilities, primarily supporting simple filters and projections. They cannot perform complex joins or window functions that are often required in transformation pipelines, making them unsuitable as a general-purpose tool for replacing complex ETL logic with automatic updates.
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Stored Procedures
Why it's wrong here
Stored Procedures are imperative blocks of code that require manual invocation or scheduling via Tasks. They do not have an inherent 'automatic update' mechanism based on source data changes. They are useful for complex procedural logic but do not offer the declarative simplicity of Dynamic Tables.
About these practice questions
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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
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