Google Cloud Professional Data Engineer Exam

What tool should business analysts use for repeatable and automated data cleaning tasks?

1. Create a Dataflow pipeline

2. Load the data into Dataprep

3. Run a Dataproc job

4. Explore the data with Google Sheets

The correct answer is: Load the data into Dataprep

Business analysts looking to perform repeatable and automated data cleaning tasks would find Dataprep to be the most suitable tool. Dataprep is a visual data preparation tool that enables users to clean, enrich, and transform datasets efficiently and intuitively. It is designed specifically for analysts and non-technical users, allowing them to perform data cleaning tasks without extensive coding or complex configurations. The tool supports automation through features such as visual recipes, where users can create step-by-step instructions for data preparation. These recipes can be saved and reused, making it easy for analysts to apply the same cleaning steps to new datasets in the future. This repeatability is essential for maintaining consistency in data quality across analysis projects. In contrast, while a Dataflow pipeline is powerful for processing large amounts of streaming or batch data, it typically requires more advanced programming skills and is more suited for developers. Running a Dataproc job involves managing a cluster for processing data using Apache Spark, which again may not align with the needs of business analysts needing simple cleaning mechanisms. Exploring data with Google Sheets can help with light data manipulation and visualization, but it lacks the automated and robust capacity that Dataprep offers for systematic data cleaning tasks.