CERTIFIED-DATA-ANALYST-ASSOCIATE Question #72: Real Exam Question with Answer & Explanation

Question

How should Databricks SQL be used in relation to other business intelligence (BI) tools like Tableau, Power BI, and Looker?

Options

• AAs a complementary tool for quick in-platform BI work
• BAs a complete replacement with additional functionality
• CAs an exact substitute with the same level of functionality
• DAs a complementary tool for professional-grade presentations

Explanation

A is correct because Databricks SQL is designed to work alongside dedicated BI tools - it provides in-platform querying, dashboards, and visualizations for data teams who want quick analytical work without leaving the Lakehouse environment, but it doesn't try to replace the mature ecosystems of Tableau, Power BI, or Looker.

B is wrong because Databricks SQL lacks the full feature depth of dedicated BI platforms - things like advanced report formatting, enterprise distribution workflows, and rich visualization libraries that tools like Tableau or Power BI have built over years.

C is wrong because "exact substitute with the same level of functionality" implies feature parity, which doesn't exist - Databricks SQL is purposefully scoped for in-platform analytics, not as a drop-in replacement.

D is wrong because it mischaracterizes the use case - "professional-grade presentations" describes dedicated BI tools (Tableau, Power BI), not Databricks SQL, which targets data engineers and analysts doing exploratory or operational queries rather than polished stakeholder reporting.

Memory tip: Think of Databricks SQL as the "quick look" tool - it complements BI tools the same way a whiteboard complements a formal slide deck. It's fast and in-context, but you still need the dedicated tool for the polished final product.

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