[100% Off] Databricks Certified Data Analyst Associate Practice Exams

Up-to-date practice tests with detailed explanations, exam tips, and full coverage of all exam domain

Added on September 20, 2025 IT & Software 2 min read

What you’ll learn

Interpret exam domains
weightings
and question styles.
Identify key strategies for answering scenario-based and multiple-response exam questions.
Recognize how each exam topic maps to real-world adoption and business use cases.
Apply exam-taking techniques and timing tips to maximize performance on the official certification.

Requirements

A strong motivation to pass the exam.

Description

The Certified Data Analyst Associate (CDA-A) credential validates an individual’s ability to collect, clean, transform, and interpret data to generate meaningful insights for business and technical stakeholders. It is designed for junior data analysts, business intelligence professionals, and aspiring data scientists who want to demonstrate their competency in core data analysis skills and tools used in modern analytics environments.

The CDA-A exam ensures that candidates understand data structures, query languages, visualization techniques, and statistical foundations necessary to turn raw data into actionable information. This certification also covers ethical data handling and communication best practices to support informed decision-making.

Key knowledge areas include:

Data Collection & Cleaning: sourcing data from spreadsheets, databases, APIs, and cloud storage; handling missing values, duplicates, and outliers.
Data Transformation: applying filters, joins, aggregations, and pivot operations using SQL and analytics tools; reshaping datasets for analysis.
Exploratory Data Analysis (EDA): using descriptive statistics, distributions, and correlation measures to identify patterns and trends.
Visualization & Reporting: creating dashboards and visualizations (charts, graphs, KPIs) in tools like Tableau, Power BI, or Python libraries (Matplotlib, Seaborn).
Basic Statistical Analysis: hypothesis testing, sampling, and confidence intervals to validate insights.
Data Ethics & Governance: applying data privacy principles, ensuring compliance, and presenting results responsibly.
Communication of Insights: summarizing findings for non-technical audiences, creating compelling narratives, and building data-driven recommendations.
Introductory Automation & Scripting: using Excel macros, SQL procedures, or Python/R scripts to streamline repetitive tasks.

The CDA-A practice tests replicate real-world scenarios such as cleaning a messy dataset, running a complex SQL query to answer a business question, designing a visualization to show trends over time, or interpreting statistical test results. Each question includes a detailed explanation, reinforcing both technical steps and analytical thinking.

By earning the CDA-A, professionals demonstrate the ability to transform raw data into actionable insights, making them valuable contributors to analytics teams. This certification is ideal for roles such as Junior Data Analyst, BI Associate, Reporting Specialist, or Marketing Analyst, and it serves as a stepping stone toward advanced analytics or data science certifications.