Question 4

Explanation

Option A is CORRECT. Cloud Dataprep by Trifacta provides a visual, interactive interface specifically designed for data preparation without requiring coding skills. It automates schema detection, suggests transformations for cleaning and standardizing data, and allows users to see transformation results in real-time. This makes it ideal for standardizing different data formats from multiple sources, providing the most user-friendly approach for business analysts who may not have extensive programming experience.

Option B is INCORRECT. While BigQuery SQL can perform transformations, writing complex SQL to standardize different data formats requires significant technical expertise. This approach lacks the visual, intuitive interface that would make the task more accessible to users without advanced SQL skills.

Option C is INCORRECT. Cloud Dataflow requires writing code in Java or Python using the Apache Beam SDK. This is not user-friendly for business analysts who may not have programming skills, and requires more development effort compared to a visual tool like Dataprep.

Option D is INCORRECT. Cloud Functions would require writing custom code for transformations and setting up triggers for each data source. This approach lacks a unified interface for data preparation and would be complex to maintain for 300 stores sending data in different formats.