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Big Data & Cloud Analytics Flashcards

7 cards from real DAC practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 7 Big Data & Cloud Analytics flashcards as text

  1. What is a common advantage of separating storage from compute in cloud analytics architectures?

    Answer: Each can scale independently to control cost

    Decoupling storage and compute lets each scale independently, optimizing performance and cost.

  2. In MapReduce, what is the role of the 'reduce' phase?

    Answer: Aggregate and combine intermediate results by key

    The reduce phase aggregates the intermediate key-value pairs produced by the map phase.

  3. Which concept describes ingesting data continuously as it is generated rather than in scheduled batches?

    Answer: Real-time streaming ingestion

    Real-time streaming ingestion processes data continuously as events occur.

  4. A data engineer needs sub-millisecond key-based lookups for a caching layer. Which store fits best?

    Answer: Redis (in-memory key-value store)

    Redis is an in-memory key-value store ideal for extremely fast key-based lookups and caching.

  5. What is the main benefit of partitioning a large table in a cloud data warehouse?

    Answer: Queries can prune irrelevant partitions to scan less data

    Partitioning lets the engine skip (prune) partitions that don't match the query, reducing data scanned.

  6. Which term refers to the process of extracting, transforming, and loading data into a warehouse?

    Answer: ETL

    ETL stands for Extract, Transform, Load — the classic data integration pipeline.

  7. In a modern 'ELT' pattern, where does the transformation typically happen compared to ETL?

    Answer: Inside the target warehouse after loading raw data

    In ELT, raw data is loaded first and transformed inside the powerful target warehouse.