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CompTIA DataX

Exam Code : DY0-001

The CompTIA Cloud+ Certification is designed to validate your skills in managing and optimizing cloud infrastructure. It covers essential areas such as cloud architecture, deployment, security, troubleshooting, and operations. This certification is ideal for IT professionals looking to prove their expertise in cloud technologies and advance their careers in the growing cloud computing industry. By earning this certification, you gain the knowledge to handle cloud systems, enhance security, and ensure the effective operation of cloud-based environments.

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Why Join this Program

  • Build Strong Data Foundations
    The program equips you with essential skills in data analysis, data management, and interpretation—skills that are vital across industries in today’s data-driven world.

  • Get Industry-Recognized Validation
    CompTIA DataX is a globally respected certification that validates your ability to work with data, enhancing your credibility and career prospects in a competitive job market.

  • Bridge the Gap Between Business and Data
    Learn how to turn raw data into actionable insights, improving decision-making and helping organizations drive success using data-driven strategies.

  • Open Doors to Diverse Roles
    Whether you’re entering IT, marketing, finance, or healthcare, this certification prepares you for roles such as data analyst, reporting specialist, or business intelligence associate.

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Program Overview

The CompTIA DataX Certification is designed for professionals aiming to build a strong foundation in data management and analytics. This program focuses on developing essential skills such as data mining, data governance, data analysis, and data visualization. It ensures learners understand how to interpret data responsibly, manage data lifecycles, and apply analytical techniques using real-world tools.

Ideal for those pursuing roles in data analytics, business intelligence, or data science, the DataX certification validates your ability to make data-driven decisions, manage structured and unstructured data, and support organizational goals through data insights. This program equips learners with the practical knowledge needed to work confidently with data in today’s digital economy.

Key Features

  • Industry-Recognized Credential – Globally respected certification that validates foundational data analytics and data literacy skills.

  • Comprehensive Coverage – Covers core topics such as data mining, data governance, data visualization, and analytics processes.

  • Tool-Agnostic Approach – Teaches fundamental data concepts without being tied to specific platforms or tools, ensuring broad applicability.

  • Focus on Data Ethics and Governance – Emphasizes responsible data use, data privacy, and ethical decision-making.

  • Hands-On Skill Development – Encourages practical learning through scenario-based questions and real-world use cases.

  • Supports Career Growth – Prepares learners for entry-level to intermediate data roles such as Data Analyst and Business Intelligence Specialist.

  • Mapped to Data Lifecycle – Aligned with the entire data lifecycle: collection, analysis, interpretation, and reporting.

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  • Aligned with Employer Needs – Developed with input from data professionals and organizations to match current industry expectations.

  • Prepares for Future Learning – Acts as a stepping stone toward more advanced certifications in data science and analytics.

  • Flexible Learning Options – Available through self-paced online learning, instructor-led training, and other flexible modalities.

Learning Path

1.0 Mathematics and Statistics (17%)

1.1 Given a scenario, apply the appropriate statistical method or concept.
1.2 Explain probability and synthetic modeling concepts and their uses.
1.3 Explain the importance of linear algebra and basic calculus concepts.
1.4 Compare and contrast various types of temporal models.

2.0 Modeling, Analysis, and Outcomes (24%)

2.1 Given a scenario, use the appropriate exploratory data analysis (EDA) method or process.
2.2 Given a scenario, analyze common issues with data.
2.3 Given a scenario, apply data enrichment and augmentation techniques.
2.4 Given a scenario, conduct a model design iteration process.
2.5 Given a scenario, analyze results of experiments and testing to justify final model recommendations and selection.
2.6 Given a scenario, translate results and communicate via appropriate methods and mediums.

3.0 Machine Learning (24%)

3.1 Given a scenario, apply foundational machine-learning concepts.
3.2 Given a scenario, apply appropriate statistical supervised machine-learning concepts.
3.3 Given a scenario, apply tree-based supervised machine-learning concepts.
3.4 Explain concepts related to deep learning.
3.5 Explain concepts related to unsupervised machine learning.

4.0 Operations and Processes (22%)

4.1 Explain the role of data science in various business functions.
4.2 Explain the process of and purpose for obtaining different types of data.
4.3 Explain data ingestion and storage concepts.
4.4 Given a scenario, implement common data-wrangling techniques.
4.5 Given a scenario, implement best practices throughout the data science life cycle.
4.6 Explain the importance of DevOps and MLOps principles in data science.
4.7 Compare and contrast various deployment environments.

5.0 Specialized Applications of Data Science (13%)

5.1 Compare and contrast optimization concepts.
5.2 Explain the use and importance of natural language processing (NLP) concepts.
5.3 Explain the use and importance of computer vision concepts.
5.4 Explain the purpose of other specialized applications in data science.

What Skills Will You Learn?

  • Data Literacy
    Understand data types, structures, and the data lifecycle to interpret and work effectively with data in any organization.

  • Data Mining and Exploration
    Learn how to collect, clean, and prepare data for analysis using various tools and techniques.

  • Data Analysis and Interpretation
    Gain proficiency in analyzing datasets to uncover trends, patterns, and insights that inform business decisions.

  • Data Visualization
    Master tools like Excel, Power BI, or Tableau to create compelling charts, dashboards, and reports for stakeholders.

  • Data Governance and Quality
    Understand the importance of data accuracy, consistency, and integrity through proper data governance practices.

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  • Data-Driven Decision-Making
    Learn how to apply critical thinking and analytical skills to solve real-world problems using data insights.

  • Basic Statistical Techniques
    Apply descriptive and inferential statistics to evaluate data and support findings.

  • Data Security and Compliance
    Learn the basics of securing data and ensuring compliance with regulations such as GDPR or HIPAA.

Jobs You Can Land with the CompTIA DataX certification:

  • Data Analyst
    Interpret complex datasets, create reports, and help organizations make data-driven decisions.

  • Business Intelligence (BI) Analyst
    Develop dashboards and visualizations to provide insights into business performance and trends.

  • Data Technician
    Manage data systems, organize datasets, and ensure data accuracy for analysis and reporting.

  • Operations Analyst
    Use data to streamline operations, identify inefficiencies, and support process improvements.

  • Reporting Analyst
    Generate reports from various data sources to assist stakeholders in evaluating business activities.

  • Data Support Specialist
    Provide technical support in data collection, entry, validation, and maintenance.

  • Market Research Analyst
    Analyze market trends and customer data to support marketing and product strategies.

  • Junior Data Engineer
    Assist in building and maintaining data pipelines and ETL processes.

  • Financial Analyst (Entry-Level)
    Use data to track financial performance, forecast trends, and support budgeting decisions.

  • Healthcare Data Analyst
    Work with healthcare data to improve patient outcomes, reduce costs, and support compliance.

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Exam Details

Course NameCompTIA DataX 
Course Number:DY0-001 
Required examDY0-001 
Number of QuestionsMaximum of 90 questions 
Type of QuestionsMultiple-choice and performance-based 
Length of Test165 Minutes 
Passing ScorePass/Fail only (no scaled score) 
RetirementUsually three years after launch 
LanguagesEnglish

Exam Preparation

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