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Databricks-DE-Pro Data Transformation, Cleansing, Quality Practice Question

Which TWO statements regarding the use of 'APPLY CHANGES INTO' in Delta Live Tables (DLT) are correct?

⚠ Common exam trap

Candidates often assume 'APPLY CHANGES INTO' works on static tables or supports manual deletes. They frequently overlook that it is designed specifically for streaming, SCD-based incremental updates.

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

✓

It supports schema evolution automatically when adding new columns to the source stream.

APPLY CHANGES INTO is the declarative mechanism for SCD Type 1 or Type 2 processing in DLT. It manages the complexity of merging streaming data into a target table, handling late-arriving data and updates efficiently. Understanding its constraints, such as the requirement for a defined primary key and the inability to perform manual data deletions, is critical for maintaining consistent state in bronze-to-silver transformations.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ✓

    It supports schema evolution automatically when adding new columns to the source stream.

    Why this is correct

    APPLY CHANGES INTO inherently supports schema evolution, allowing the target table to adapt to new columns present in the source stream. This is essential for long-running pipelines where source data structures might change over time, ensuring that the target reflects the latest source state without requiring manual intervention.

  • ✗

    It can be used to perform deletes on the target table by issuing manual DELETE commands.

    Why it's wrong here

    APPLY CHANGES INTO does not support manual DELETE commands within the DLT pipeline logic. The target table should be treated as managed by the DLT engine. If data removal is required, it must be handled through the logic defined within the APPLY CHANGES block using appropriate flags.

  • ✓

    It requires the source to be a streaming table or a view registered in the pipeline.

    Why this is correct

    To maintain the state and process changes correctly, the source must be defined within the DLT graph. Using a streaming source ensures that the CDC (Change Data Capture) information is processed in the order it arrives, which is a fundamental requirement for accurate SCD Type 2 history tracking.

  • ✗

    It allows for multiple primary keys, but only one can be used for sequencing the updates.

    Why it's wrong here

    The KEYS clause in APPLY CHANGES INTO expects a defined set of columns that uniquely identify the record. While it supports composite keys, it does not distinguish between 'primary' and 'sequencing' keys in the manner described. Sequencing is handled by a separate SEQUENCE BY clause for timestamp-based ordering.

  • ✗

    It automatically creates a history table for SCD Type 1 processing by default.

    Why it's wrong here

    SCD Type 1 processing performs an 'overwrite' of existing records, meaning history is not preserved. History tables are specifically a feature of SCD Type 2 implementations, where the history is tracked via additional columns like valid_from and valid_to, rather than being an automatic default for all types.

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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 Databricks exam blueprint

This Databricks-DE-Pro practice question is part of Courseiva's free Databricks 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 Databricks-DE-Pro exam.