Answer: Testing the quality of data as it is imported from a source

The question asks for a common analytics application that can be completed using Databricks SQL. Databricks SQL is specifically designed for SQL-based analytics, data exploration, and reporting on data stored in the Databricks Lakehouse. Option C, 'Testing the quality of data as it is imported from a source,' is a typical use case for Databricks SQL, as it involves running SQL queries to validate data integrity, check for nulls, duplicates, or format inconsistencies during data ingestion. This aligns with Databricks SQL's role in data quality checks and exploratory analysis. In contrast, Option A involves augmenting data with external sources, which may require more complex ETL workflows beyond pure SQL. Option B focuses on automating notebook-based workflows, which is better suited to Databricks Notebooks or Workflows, not Databricks SQL. Option D, customer segmentation via clustering, typically uses machine learning algorithms (e.g., in Databricks ML), not standard SQL analytics. The community discussion shows 100% consensus on C, with upvoted comments supporting it as the correct answer, reinforcing its suitability.

Author: LeetQuiz Editorial Team