Google Professional Data Engineer Question 22
Select 2Google Cloud PlatformYour organization has data stored in CSV format on Google Cloud Storage. The data contains some missing values, duplicate rows, and inconsistent date formats. You need to prepare and clean this data for analysis. Which tool(s) should you use to address these issues efficiently while minimizing development effort?
- A
Cloud Dataprep
- B
Cloud Data Fusion
- C
Cloud Dataflow
- D
BigQuery
Show answer and explanation
Correct answers: A, B
Explanation
Cloud Dataprep and Cloud Data Fusion are the most appropriate tools for preparing and cleaning data with minimal development effort. Both provide user-friendly interfaces for performing common cleaning tasks such as handling missing values, removing duplicates, and standardizing formats. Cloud Dataflow and BigQuery, while powerful, are not optimized for these tasks in this scenario.
- A. Correct.
Cloud Dataprep is a suitable choice for cleaning and preparing data with a user-friendly interface. It can handle tasks like removing duplicates, filling missing values, and standardizing date formats without requiring code.
- B. Correct.
Cloud Data Fusion is a data integration service that provides a GUI-based approach to transform and prepare data. It is particularly useful for creating data pipelines without writing extensive custom code.
- C. Incorrect.
Cloud Dataflow is a fully managed service for stream and batch data processing. While it is powerful, it requires custom programming and doesn’t provide a simple user interface for tasks like cleaning and preparation, making it less efficient for this specific scenario.
- D. Incorrect.
BigQuery is a fully managed data warehouse and can be used for querying and analyzing data. However, it is not primarily designed for data cleaning and preparation tasks, which would require additional scripting or transformation steps.