Databricks Certified Data Engineer - Associate
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Ultimate access to all questions.
In the context of the Databricks Lakehouse Platform, consider a scenario where a data engineering team is tasked with migrating their traditional SQL analytics workloads to a more scalable and performant solution. The team is evaluating Databricks SQL Analytics for its potential benefits over their current setup. Which of the following statements accurately describes how Databricks SQL Analytics works and its advantages compared to traditional SQL analytics solutions? Choose the best option.
A
Databricks SQL Analytics functions similarly to traditional SQL analytics solutions by allowing SQL queries on data, but it lacks any specific optimizations for big data, making it unsuitable for large-scale analytics workloads.
B
Databricks SQL Analytics enables SQL query execution on big data with optimizations for performance and scalability, offering a significant improvement over traditional SQL analytics solutions by leveraging the Lakehouse architecture for efficient data processing and analytics.
C
Databricks SQL Analytics is designed for manual data analysis tasks only, providing no performance or scalability benefits over traditional SQL analytics solutions, thus not suitable for big data analytics.
D
Databricks SQL Analytics replaces traditional SQL analytics solutions by offering a completely manual data analysis approach, which, despite being more time-consuming, ensures higher accuracy in data analysis tasks.