CompTIA Data+

CompTIA Data+ certification validates the skills of early-career professionals to analyze, interpret, and communicate data effectively, enabling informed, data-driven business decisions and demonstrat

CompTIA Data+

Course Overview

CompTIA Data+ is an entry-level certification designed for professionals seeking to enhance their data analytics skills and support data-driven business decision-making. This certification validates essential data analysis, visualization, and reporting competencies, making it ideal for individuals looking to build a strong foundation in data analytics.

At Emigo Networks, we offer comprehensive training for CompTIA Data+, equipping learners with the knowledge and hands-on expertise needed to interpret and analyze data effectively. Our expert-led training program ensures that participants gain practical insights and industry-relevant skills to excel in data analytics roles.

What You'll Learn

Understand core data concepts by identifying data schemas, dimensions, and differentiating between common data structures and file formats.
Perform data acquisition and preparation including cleansing, profiling, and manipulation to improve data quality and mining skills.
Apply statistical methods and critical analysis techniques to summarize, interpret, and extract meaningful insights from data.
Translate business requirements into visual insights by creating effective reports, dashboards, and visualizations.
Implement data governance and quality control to ensure compliance, accuracy, and reliability in data-driven decision-making.

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Syllabus Summary

Data concepts and environments

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 mining

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.

Data analysis

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.

Visualization

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, quality, and controls

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.

Pre-requisites

Approximately 18–24 months of experience in a report or business analyst role, involving data analysis and reporting tasks.
Exposure to databases and analytical tools, with a basic understanding of statistics and data visualization techniques.
Familiarity with data concepts and environments, including data schemas, dimensions, and various data structures and file formats.
Experience in data mining and manipulation, encompassing data acquisition, cleansing, profiling, and applying basic statistical methods.
Ability to translate business requirements into visual insights, by creating effective reports, dashboards, and visualizations.
Understanding of data governance and quality control, ensuring compliance and accuracy in data-driven decision-making.

Required Exams

Exam: DA0-001
Cost: $255 USD
Duration: 90 minutes

Who Should Attend

CompTIA Data+ is designed for professionals seeking to develop and promote data-driven business decision-making. This certification is ideal for:

Early-career data analysts looking to validate their skills in data analysis and reporting.
Business analysts who wish to enhance their ability to interpret and communicate data insights.
Project managers interested in integrating data analytics into project planning and execution.
Individuals transitioning into data-focused roles from other disciplines.

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What is CompTIA Data+ Certification?

CompTIA Data+ (DA0-001) is a professional certification designed for data professionals. It validates the skills required for data analysis, visualization, reporting, data governance, and quality control.
This certification is ideal for professionals who work with data-driven decision-making and business intelligence.

Who is the target audience for the CompTIA Data+ exam?

Data Analysts
Business Intelligence (BI) Professionals
Data Scientists (Entry Level)
Marketing and Financial Analysts
Database Administrators
IT and Cybersecurity Professionals handling data analysis

What are the prerequisites for the CompTIA Data+ exam?

CompTIA recommends 1.5–2 years of experience in a data analyst or business analyst role.
Basic understanding of databases, data visualization, and statistical analysis is beneficial.
Familiarity with Excel, SQL, and data visualization tools (Power BI, Tableau) is useful but not mandatory.

What topics are covered in the CompTIA Data+ exam?

The exam focuses on the following domains:

Data Concepts and Environments (15%) – Data structures, databases, and types of data.
Data Mining (25%) – Extracting, querying, and transforming data.
Data Analysis (23%) – Statistical methods, data validation, and interpretation.
Visualization (23%) – Creating dashboards, charts, and presenting data effectively.
Data Governance, Quality, and Control (14%) – Security, compliance, and data integrity.

How is the CompTIA Data+ exam structured?

Exam Code: DA0-001
Number of Questions: 90
Question Type: Multiple-choice and performance-based questions
Exam Duration: 90 minutes
Passing Score: 675 out of 900

How do I register for the CompTIA Data+ exam?

The exam can be scheduled through Pearson VUE testing centers or taken online.
Emigo Networks provides guidance on registration and may offer exam vouchers as part of its training packages.

What is the cost of the CompTIA Data+ exam?

The exam fee is approximately $246 USD, but it may vary by location.
Emigo Networks may offer bundled training programs that include exam vouchers at discounted rates.

What training resources does Emigo Networks provide for CompTIA Data+?

Instructor-led training – Live sessions with expert trainers.
Hands-on Labs – Practical exercises in data analysis and visualization tools.
Study Materials & Exam Prep – Access to practice exams, study guides, and quizzes.
Real-world Scenarios – Training on real-life data projects to enhance practical knowledge.

How long is the CompTIA Data+ certification valid for?

The CompTIA Data+ certification is valid for three (3) years.
Renewal is possible through CompTIA’s Continuing Education (CE) program, where candidates can earn CEUs (Continuing Education Units) or retake the latest version of the exam.

Can Emigo Networks help with post-certification support?

Yes, Emigo Networks provides:

Job assistance and placement support for certified professionals.
Resume-building and interview preparation for data-related roles.
Networking opportunities to connect with industry professionals.

Are there any discounts or promotions for CompTIA Data+ training at Emigo Networks?

Emigo Networks occasionally offers seasonal discounts, corporate training packages, and bundled offers for multiple CompTIA certifications.
You can check for ongoing promotions directly through Emigo Networks' website or by contacting their training team.

What is the format of CompTIA Data+ training at Emigo Networks?

Classroom-based Training – In-person training with hands-on practice.
Virtual Instructor-Led Training (VILT) – Live online sessions for remote learning.
Self-paced Learning – Access to recorded lessons and study materials for flexible learning.

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