Google Cloud Professional Data Engineer Exam

Which tool should your data analysts use to build data pipelines with a graphical interface?

1. Cloud Composer

2. Dataflow

3. Cloud Data Fusion

4. Dataproc

The correct answer is: Cloud Data Fusion

Using Cloud Data Fusion is an ideal choice for data analysts who need to build data pipelines with a graphical interface. This tool provides a user-friendly, drag-and-drop interface that allows analysts to visually design and orchestrate data workflows easily, without requiring extensive programming knowledge. Cloud Data Fusion supports the integration of various data sources and various transformations, streamlining the process of building complex data pipelines. It also features a wide array of pre-built connectors, making it simple to connect to different data stores and services, facilitating timely data ingestion and processing. In comparison, while Cloud Composer is a powerful orchestration tool based on Apache Airflow for managing workflows, it is less focused on providing a graphical interface for analysts, primarily targeting data engineers and developers who are comfortable with coding. Dataflow is designed for real-time stream and batch data processing, but it does not provide a graphical interface, requiring users to rely more on code for setup and management. Dataproc is specifically for running Apache Spark and Hadoop clusters; it offers powerful big data processing capabilities but lacks a dedicated graphical interface for building data pipelines in the way that Cloud Data Fusion does. Thus, Cloud Data Fusion stands out as the appropriate tool for data analysts looking for a graphical way to design and manage data