You store historic data in Cloud Storage. You need to perform analytics on the historic data. You want to use a solution to detect invalid data entries and perform data transformations that will not…

Question

Options

• AUse Cloud Dataflow with Beam to detect errors and perform transformations.
• BUse Cloud Dataprep with recipes to detect errors and perform transformations.
• CUse Cloud Dataproc with a Hadoop job to detect errors and perform transformations.
• DUse federated tables in BigQuery with queries to detect errors and perform transformations.

• A
  10% (2)
• B
  81% (17)
• C
  5% (1)
• D
  5% (1)

Explanation

Cloud Dataprep is purpose-built for data wrangling by non-technical users - it uses a visual, recipe-based interface where you can detect anomalies, clean data, and transform it without writing a single line of code or SQL.

• A is wrong - Cloud Dataflow with Apache Beam requires writing pipeline code (Java, Python, or Go), making it unsuitable for users without programming skills.
• C is wrong - Cloud Dataproc runs Hadoop/Spark jobs, which absolutely require programming expertise.
• D is wrong - Federated tables in BigQuery still require SQL queries to detect errors and transform data.

Memory tip: Think of "Dataprep = Data Preparation for non-programmers." The word recipe is the giveaway - just like a cooking recipe requires no technical expertise, Dataprep recipes let analysts visually build transformation steps step-by-step. Whenever an exam question says "no programming, no SQL," Dataprep is almost always the answer.

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