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CompTIA Data+ - United Arab Emirates

  • 4.8(498056 Rating)

Duration

5 days

Language

English / Arabic

Batch Options

4 hours & 8 hours

Upcoming Batch

17 November 2025
Overview Schedule Dates Course Content FAQs

Course Overview

CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. Equip yourself with skills to better analyze and interpret data, communicate insights, and demonstrate competency. CompTIA Data+ validates that certified professionals have the skills required to facilitate data-driven business decisions.

Skills Learned

  • Identify basic concepts of data schemas and dimensions, and understand the differences between common data structures and file formats to build a strong foundation in data concepts and environments.
  • Apply data acquisition, cleansing, profiling, and manipulation techniques to enhance data mining skills.
  • Use appropriate descriptive statistical methods and summarize types of analysis and critical analysis techniques for effective data analysis.
  • Translate business requirements into meaningful visualizations by creating reports or dashboards.
  • Summarize key data governance concepts and apply data quality control techniques to ensure accuracy and compliance.

Exam Details

  • Exam version: V1
  • Exam series code: DA0-001
  • Launch date: February 28, 2022
  • Number of questions: a maximum of 90 questions
  • Types of questions: multiple-choice and performance-based
  • Duration: 90 minutes
  • Passing score: 675 (on a scale of 100-900)
  • Languages: English, Japanese, and Thai
  • Recommended experience: 18–24 months in a report or business analyst job role, with exposure to databases and analytical tools, a basic understanding of statistics, and data visualization experience
  • Retirement: usually three years after launch (estimated 2025)

Career Path

Flexible Training Options to
Meet Your Needs

We understand that flexibility is key to effective learning and development, especially in today’s dynamic work environment. That’s why we offer multiple delivery formats for our trainings in UAE. Whether you prefer the interaction of in-person classes, the convenience of live virtual training, or the independence of self-paced online learning, we have a solution tailored to your schedule. Our goal is to make professional growth accessible to everyone, allowing you to upskill without compromising your other commitments.

Online Instructor Led

Learn from the comforts of your home/office with our expert trainers via online platforms.

Classroom Training

Face-to-face physical classroom training with max interactions at our 5* training venues.

Onsite Training

Learn in your own environment from our expert trainers for maximum impact.

Overseas Training

Choose your desired country for learning with our expert trainers.

Target Audiance

  • Data Analysts
  • Database Administrators
  • Data Engineers
  • Business Analyst
  • Entry-level Data Scientists
  • Systems Analysts
  • IT Managers
  • Data Consultants
This course includes:
  • Soft copy of Courseware
  • Certificate of Course Complition
  • Experienced and Professional Trainer
  • Lab and Exercises During Training
  • Sample Questions for Exam Prepration
  • Mock Test on the Last Day of Training
  • Exam Registration Guidance
  • 5-Star Training Environmment
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Schedule Dates

17 November 2025 - 21 November 2025
CompTIA Data+
23 February 2026 - 27 February 2026
CompTIA Data+
25 May 2026 - 29 May 2026
CompTIA Data+
31 August 2026 - 04 September 2026
CompTIA Data+

Course Content

  • Data schemas and dimensions: identifying databases, data marts, data warehouses, data lakes, and slowly changing dimensions.
  • Data types: comparing date, numeric, alphanumeric, currency, text, discrete vs. continuous, categorical/dimension, images, audio, and video.
  • Data structures and file formats: comparing structured and unstructured data and file formats like text/flat files, JavaScript object notation (JSON), extensible markup language (XML), and hypertext markup language (HTML).

  • Data acquisition: explaining integration methods like delta load, extract/load/transform (ELT), and collection methods like web scraping, application programming interfaces (APIs), surveys, sampling, and observation.
  • Data cleansing and profiling: identifying duplicate data, missing values, invalid data, outliers, specification mismatches, and data type validation.
  • Data manipulation techniques: executing techniques like merging, blending, concatenation, appending, imputation, aggregation, transposing, normalizing, and parsing.
  • Query optimization: explaining filtering, sorting, date functions, logical functions, aggregate functions, indexing, temporary tables, and execution plans.

  • Descriptive statistics: applying measures of central tendency, dispersion, frequencies, percentages, percent change, and confidence intervals.
  • Inferential statistics: explaining t-tests, z-scores, p-values, chi-squared tests, hypothesis testing, regression, and correlation.
  • Analysis techniques: summarizing trend analysis, performance analysis, exploratory analysis, and link analysis.

  • Business requirements: translating requirements into reports using measures of central tendency, dispersion, and percentages.
  • Report and dashboard design: using cover pages, design elements, and documentation.
  • Dashboard development: applying considerations for development processes and delivery.
  • Visualization types: applying line charts, pie charts, scatter plots, bar charts, histograms, heat maps, geographic maps, tree maps, stacked charts, and word clouds.
  • Report types: comparing static vs. dynamic, ad-hoc, self-service, recurring, and tactical research reports.

  • Data governance: summarizing access, security, storage, use, entity relationships, classification, jurisdiction, and breach reporting.
  • Data quality control: applying validation methods, quality dimensions, rules, metrics, and automated checks.
  • Master data management (MDM): explaining processes and circumstances for MDM.

FAQs

The CompTIA Data+ course provides professionals with essential skills in data literacy, analysis, and interpretation, enabling them to make data-driven decisions, apply governance practices, and communicate insights effectively.

Although no formal prerequisites are required, it is recommended that learners have 18–24 months of hands-on experience in a data-related role, along with basic knowledge of databases, statistics, and business intelligence tools.

Yes. Data+ strikes a balance between technical data skills (such as queries and data modelling) and business intelligence (such as presenting findings and driving decision-making).

It validates your ability to handle data confidently, positioning you for roles such as Data Analyst, Business Intelligence Analyst, Reporting Analyst, or Data Governance Specialist.

Yes. Data+ can serve as a foundation for advanced certifications such as Microsoft Data Analyst Associate, Google Data Analytics Professional, or even more specialised paths like Certified Analytics Professional (CAP).

Yes. The curriculum includes modules on presenting insights effectively to both technical and non-technical audiences, an essential skill for influencing business decisions.

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