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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 — missed cards come back until you master them.

Read the first 7 ETL and ELT Pipelines flashcards as text
  1. Backfilling a pipeline refers to what activity?

    Answer: Reprocessing historical date ranges to populate or correct past data

    Backfilling runs the pipeline over past periods to fill gaps or apply corrected logic retroactively.

  2. Which file format is columnar and well-suited for analytical ELT workloads?

    Answer: Apache Parquet

    Parquet stores data by column with compression and predicate pushdown, ideal for analytics.

  3. What is the benefit of partitioning a large table by date in a warehouse?

    Answer: Queries can prune irrelevant partitions, scanning less data

    Date partitioning lets the engine skip partitions outside the query's range, cutting scan cost.

  4. A watermark in stream processing is primarily used to do what?

    Answer: Track event-time progress and decide when a window can close

    Watermarks signal how far event-time has advanced, allowing windows to finalize despite out-of-order data.

  5. Which delivery guarantee can produce duplicate records that downstream logic must deduplicate?

    Answer: At-least-once delivery

    At-least-once may redeliver messages on retry, so consumers must handle duplicates.

  6. Why is storing transformation logic as version-controlled code (e.g., dbt models) preferred over manual SQL scripts?

    Answer: It enables testing, code review, lineage, and reproducible deployments

    Code-based transformations bring software engineering rigor—tests, reviews, lineage—to the warehouse layer.

  7. A surrogate key in a data warehouse dimension is best described as what?

    Answer: A system-generated identifier independent of business values

    Surrogate keys are warehouse-assigned integers that stay stable even when natural business keys change.