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ETL and ELT Pipelines Flashcards

7 cards from real Data Engineering practice questions. Tap to flip, then mark Knew It or Still Learning โ€” missed cards come back until you master them.

Read the first 7 ETL and ELT Pipelines flashcards as text
  1. Which orchestration tool models pipelines as Directed Acyclic Graphs (DAGs) of tasks?

    Answer: Apache Airflow

    Airflow defines workflows as DAGs where each node is a task with explicit dependencies.

  2. A pipeline must process events within seconds of arrival. Which paradigm fits best?

    Answer: Streaming (real-time) processing

    Streaming processes records continuously as they arrive, achieving low end-to-end latency.

  3. In dimensional modeling, a Type 2 Slowly Changing Dimension handles updates by what method?

    Answer: Adding a new row to preserve historical versions

    SCD Type 2 inserts a new row with validity dates, keeping the full history of the attribute.

  4. What is the main risk of using SELECT * during extraction from a wide source table?

    Answer: Pulling unnecessary columns and breaking when schema changes

    SELECT * transfers all columns wastefully and makes the pipeline fragile to upstream schema changes.

  5. Which storage layer typically holds raw, unprocessed data in a modern data lakehouse pattern?

    Answer: The bronze (raw) layer

    The medallion architecture's bronze layer stores raw ingested data before refinement.

  6. A dead-letter queue in a pipeline is used to do what?

    Answer: Capture records that fail processing for later inspection

    A dead-letter queue isolates malformed or failed messages so the main flow continues uninterrupted.

  7. Which practice helps ensure data quality is verified within the pipeline itself?

    Answer: Automated data validation tests on row counts and null thresholds

    Embedding automated assertions (row counts, nulls, ranges) catches quality issues before data reaches users.