Databricks-DE-Assoc Databricks Intelligence Platform Practice Question
Which Databricks compute resource is specifically optimized for running BI dashboards and SQL queries?
⚠ Common exam trap
Candidates often confuse standard all-purpose clusters with SQL Warehouses, assuming general compute handles BI traffic equally well, ignoring the specialized query optimization and serverless scaling built specifically for dashboards.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
SQL Warehouse
Databricks SQL Warehouses are compute environments designed to deliver high-performance SQL execution, making them ideal for BI tools and dashboarding. Understanding the difference between SQL Warehouses and traditional data engineering clusters is important, as it helps engineers choose the right compute resource to match the workload, ensuring better query performance and cost efficiency for end-users who need to interact with data via SQL.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
All-Purpose Cluster
Why it's wrong here
All-Purpose clusters are designed for interactive development, debugging, and data exploration. While they can run SQL, they lack the specific optimizations found in SQL Warehouses, such as serverless scaling and specific query caching mechanisms tailored for BI dashboards, making them less efficient for high-concurrency SQL analytics environments.
- ✗
Job Cluster
Why it's wrong here
Job clusters are optimized for running automated data engineering tasks and scheduled jobs at a lower cost. They are not designed for interactive BI dashboarding or high-concurrency SQL query workloads, as their lifecycle is tied to the job execution rather than being persistent and available for dashboard user requests.
- ✓
SQL Warehouse
Why this is correct
SQL Warehouses are specifically optimized for SQL analytics. They provide features like intelligent query caching, rapid cluster startup, and auto-scaling to handle high concurrency. This makes them the primary compute choice for BI tools, SQL editors, and dashboards where low latency and high reliability are essential for end-user interaction.
- ✗
Delta Live Tables Pipeline
Why it's wrong here
Delta Live Tables is a declarative framework for building reliable data pipelines. It is used to define and manage data transformation logic and quality checks, but it is not a compute resource for executing SQL queries or powering BI dashboards for end-users, as its primary goal is efficient data ingestion.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
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