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Data Analysis & Reporting Flashcards

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

Read the first 7 Data Analysis & Reporting flashcards as text

  1. You need to run a machine learning model directly on data stored in BigQuery without exporting it. Which feature enables this?

    Answer: BigQuery ML (BQML)

    BigQuery ML allows you to create and execute machine learning models using SQL directly within BigQuery, eliminating the need to move data.

  2. What does the UNNEST() function do in BigQuery SQL?

    Answer: Flattens an array column into individual rows

    UNNEST() converts an ARRAY into a set of rows, allowing you to query individual elements of array-type columns in BigQuery.

  3. Which GCP service would you use to orchestrate a multi-step data pipeline that includes BigQuery jobs, Dataflow jobs, and Cloud Storage operations?

    Answer: Cloud Composer (Apache Airflow)

    Cloud Composer is a managed Apache Airflow service that orchestrates complex workflows across multiple GCP services with dependency management.

  4. In BigQuery, what is the difference between a clustered table and a partitioned table?

    Answer: Partitioning divides data by a column value; clustering sorts data within partitions by specified columns

    Partitioning splits a table into segments (e.g., by date), while clustering sorts the data within each partition by one or more columns to further optimize query performance.

  5. Which Looker Studio feature lets you restrict what data a specific user or group can see within a shared report?

    Answer: Row-level security via data source credentials

    Row-level security in Looker Studio is enforced at the data source level (e.g., BigQuery row-level access policies), controlling which rows each viewer can access.

  6. What is the purpose of the BigQuery Data Transfer Service?

    Answer: To automate data movement from Google and third-party sources into BigQuery on a schedule

    The Data Transfer Service automates scheduled, managed data transfers from sources like Google Ads, YouTube, and SaaS apps directly into BigQuery.

  7. When analyzing data in BigQuery, what is a 'materialized view' and its key benefit?

    Answer: A precomputed query result stored physically, auto-refreshed for faster queries

    Materialized views precompute and store query results, allowing BigQuery to serve queries faster and cheaper by reading the cached result instead of re-running the full query.