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Databricks Certified Data Analyst – 85 Practice Questions with Expert-Verified Answers – SQL, Lakehouse, Dashboards – 2025

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This document provides 85 expert-verified practice questions and answers for the Databricks Certified Data Analyst Associate exam, updated for 2025 and based on the latest Databricks Lakehouse Platform features. It serves as a comprehensive exam preparation guide covering real-world scenarios and functional knowledge across core competencies required to pass the official certification. Key topics covered include: Databricks SQL functionality: syntax, queries, permissions, user roles, scheduling dashboards, and managing SQL warehouses Lakehouse architecture: differences between lakehouse, data lake, and data warehouse models; Delta Lake capabilities; versioning and schema enforcement Data visualization and dashboards: building and sharing dashboards, alert settings, scheduling queries, and access control Data governance and access management: Unity Catalog roles, privileges, schema access levels, and query auditing Performance tuning and optimization: warehouse sizing, query cost estimation, and storage efficiency in Delta tables Practical use cases: applying filters, writing optimized SQL queries, handling nested data, and managing metadata across environments This resource is ideal for: Aspiring Databricks Certified Data Analysts Data professionals working with SQL, Spark, or Delta Lake Candidates preparing for Databricks Academy assessments Instructors or trainers developing mock exams for enterprise data tools Every question simulates the real certification exam format, providing explanations aligned with Databricks documentation and best practices. The guide ensures you're not only prepared to pass the test but also capable of applying knowledge in production environments. Keywords: Databricks SQL Unity Catalog Delta Lake Data analyst certification Lakehouse architecture SQL permissions Scheduled dashboards SQL warehouses Data governance Databricks exam prep Practice questions Schema enforcement Role-based access Metadata management Data visualization SQL alerts Performance tuning Databricks Lakehouse Access control Warehouse scaling

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Databricks Certified Data Analyst
Practice Questions 2025 Expert Verified |
Ace the Test



The data analysis team wants to perform a rapid analysis of data on the

tableau from 2 different data sources and their behavior together, what

activity would they be performing




A) Data integration

B) last-mile ETL

C) Data enhancement


D) data blending - 🧠ANSWER ✔✔D

,Which layer in the medallion architecture is best suited for ad-hoc reporting,

advanced analytics, and ML?




A) Diamond Layer

B) Bronze Layer

C) Gold Layer


D) Silver Layer - 🧠ANSWER ✔✔D


What is Delta Sharing?




A) Delta sharing allows data present in only Delta format to be sharable

inside the organization only

B) Delta Sharing is a protocol to share data present inside databricks with

other organizations

C) Delta Sharing is the industry's first open protocol for secure data

sharing, making it simple to share data with other organizations regardless

of where the data lives

,D) Delta Sharing is a protocol to share data present inside databricks within

the organizations - 🧠ANSWER ✔✔C


Which of these is the incorrect approach to handling Complex Data Types?

A) Explore and Collect

B) Support for Complex Data types is yet to be introduced

C) User Defined Function


D) Lambda Function - 🧠ANSWER ✔✔B


On the dashboard, If you have a parameter added to the dashboard, how

will it affect the visualizations:

A) The parameter will be used to fetch data for all the visualizations which

use this parameter

B) The parameter will be used to fetch data for some visualizations but not

for others though they use the same parameter

C) The parameter is not added if a parameterized query/visualization is

added

D) The parameter will not make any difference to the visualizations -

🧠ANSWER ✔✔A


3
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STATEMENT. ALL RIGHTS RESERVED

, What are the use of the Delta Lake Transaction log?




A) To provide ACID transaction capabilities

B) To track changes

C) All of the above


D) None of the above - 🧠ANSWER ✔✔C


Which of the following is NOT a benefit of data governance?

A) Consistent and high data quality for analytics and machine learning

B) Data democratization for Decision-making

C) Increased data complexity


D) Reduced time to insight - 🧠ANSWER ✔✔C


Which of the following is incorrect about Auto loader in Databricks SQL:

A) Loads json, parquet, csv files

B) Ensures file contents are loaded only once

C) Removes duplicates in the file


D) Automatically uploads files - 🧠ANSWER ✔✔C

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