CompTIA Data+ Practice Test (DA0-001)

Use the form below to configure your CompTIA Data+ Practice Test (DA0-001). The practice test can be configured to only include certain exam objectives and domains. You can choose between 5-100 questions and set a time limit.

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CompTIA Data+ DA0-001 (V1) Information

The CompTIA Data+ certification is a vendor-neutral, foundational credential that validates essential data analytics skills. It's designed for professionals who want to break into data-focused roles or demonstrate their ability to work with data to support business decisions.

Whether you're a business analyst, reporting specialist, or early-career IT professional, CompTIA Data+ helps bridge the gap between raw data and meaningful action.

Why CompTIA Created Data+

Data has become one of the most valuable assets in the modern workplace. Organizations rely on data to guide decisions, forecast trends, and optimize performance. While many certifications exist for advanced data scientists and engineers, there has been a noticeable gap for professionals at the entry or intermediate level. CompTIA Data+ was created to fill that gap.

It covers the practical, real-world skills needed to work with data in a business context. This includes collecting, analyzing, interpreting, and communicating data insights clearly and effectively.

What Topics Are Covered?

The CompTIA Data+ (DA0-001) exam tests five core areas:

  • Data Concepts and Environments
  • Data Mining
  • Data Analysis
  • Visualization
  • Data Governance, Quality, and Controls

These domains reflect the end-to-end process of working with data, from initial gathering to delivering insights through reports or dashboards.

Who Should Take the Data+?

CompTIA Data+ is ideal for professionals in roles such as:

  • Business Analyst
  • Operations Analyst
  • Marketing Analyst
  • IT Specialist with Data Responsibilities
  • Junior Data Analyst

It’s also a strong fit for anyone looking to make a career transition into data or strengthen their understanding of analytics within their current role.

No formal prerequisites are required, but a basic understanding of data concepts and experience with tools like Excel, SQL, or Python can be helpful.