Google Cloud Professional Data Engineer Exam

What is a common limitation of using Dataproc for data processing without programming knowledge?

1. Requires the use of Cloud DLP

2. Requires creating jobs in Cloud Functions

3. Does not provide a visual interface

4. Requires real-time data processing capabilities

The correct answer is: Does not provide a visual interface

Using Dataproc for data processing can be challenging for individuals without programming knowledge largely due to the lack of a visual interface. Dataproc is a managed Apache Spark and Hadoop service that allows users to process and analyze large datasets, but it is primarily designed to be operated through command-line interfaces, configuration files, and API calls, which require familiarity with programming concepts and command syntax. For users who are not comfortable with programming, this means a steep learning curve to effectively set up and manage data workflows. They may struggle to create jobs, submit them, monitor the processing, and handle output, all of which are typically done through a series of commands or scripts. Without a user-friendly visual interface that abstracts these details, users might find it daunting to leverage the full potential of Dataproc for their data processing needs. The other answer choices relate to specific capabilities or requirements of Dataproc or other Google Cloud services that do not directly address the limitations faced by users lacking programming skills. The need for real-time data processing, the requirement to create jobs in Cloud Functions, or the necessity of using Cloud DLP are not inherent limitations associated with a user's ability to interact with Dataproc without programming knowledge. Thus, the absence of a visual interface stands