English CompTIA Data +
The CompTIA Data+ exam certifies that the successful candidate possesses the essential knowledge and skills to support data-driven business decisions. It demonstrates the ability to collect, mine, and manipulate data effectively from various sources. Candidates will learn to apply basic statistical methods to interpret and analyze complex datasets. The certification ensures proficiency in transforming business requirements into actionable insights. It emphasizes adherence to data governance, quality, and security standards throughout the data life cycle. Participants will also gain the ability to visualize data and communicate findings clearly to stakeholders. Overall, CompTIA Data+ validates a professional’s capability to make informed decisions using reliable data.
- 4.8/5.0
- 1922 Eingeschrieben
- Zuletzt aktualisiert Jun 28, 2026
Kursübersicht
- CompTIA Data+ is a comprehensive data analysis certification designed for professionals responsible for collecting, analyzing, and interpreting data to drive business decisions. This certification equips you with the skills to transform complex datasets into actionable insights, apply statistical methods, and ensure data quality and governance throughout the data life cycle. By earning CompTIA Data+, you gain the confidence to perform effective data mining, create meaningful visualizations, and support data-driven strategies within your organization. The course also emphasizes practical applications, helping you bridge the gap between raw data and business decision-making. Whether you are new to data analysis or looking to validate your expertise, CompTIA Data+ provides the foundational knowledge and hands-on skills required to excel in a data-driven environment.
Kursübersicht
Identifying Basic Concepts of Data Schemas
- Understand the fundamental structures of data storage, including relational, hierarchical, and NoSQL schemas.
- Explore how data models define relationships between entities and attributes.
- Examine real-world examples of data schemas in business and analytics contexts.
Explaining Data Integration and Collection Methods
- Learn various techniques for collecting data from multiple sources, including APIs, databases, and external datasets.
- Understand ETL (Extract, Transform, Load) processes and their importance in integrating data for analysis.
- Discuss challenges in integrating heterogeneous data and best practices for resolving them.
Identifying Common Reasons for Cleansing and Profiling Data
- Explore issues such as missing values, inconsistencies, duplicates, and incorrect formatting.
- Understand the role of data profiling in evaluating data quality and identifying anomalies.
- Learn strategies to prepare data for accurate and reliable analysis.
Executing Different Data Manipulation Techniques
- Gain practical skills in transforming, filtering, aggregating, and merging datasets.
- Explore techniques for restructuring and normalizing data to suit analysis needs.
- Apply data manipulation using tools such as SQL, spreadsheets, and scripting languages.
Explaining Common Techniques for Data Manipulation and Optimization
- Learn methods for optimizing datasets to improve performance and usability.
- Understand indexing, partitioning, and other techniques for handling large-scale data efficiently.
- Explore best practices for maintaining data integrity during transformation.
Applying Descriptive Statistical Methods
- Introduce measures of central tendency, dispersion, and distribution.
- Explore visualization techniques to summarize and present data insights.
- Learn how descriptive statistics provide a foundation for advanced analytics.
Summarizing the Importance of Data Governance
- Understand policies, procedures, and standards that ensure responsible data management.
- Explore the role of compliance, security, and privacy in organizational data governance.
- Discuss how governance frameworks improve trust, accuracy, and usability of data.
Applying Quality Control to Data
- Learn techniques for validating, auditing, and monitoring data quality.
- Explore automated tools and manual processes for identifying errors and maintaining accuracy.
- Understand how continuous quality control supports reliable business decision-making.
Explaining Master Data Management Concepts
- Understand the principles of creating a single source of truth for key business entities.
- Learn strategies for maintaining consistency, accuracy, and accessibility of critical data.
- Explore integration with operational and analytical systems to support enterprise-wide decision-making.
Kursziele
On
successful completion of this course, you will be able to:
- Visualize and report data effectively by creating clear and insightful charts, dashboards, and presentations that communicate findings to both technical and non-technical stakeholders.
- Manipulate and transform data using various techniques to clean, structure, and optimize datasets for analysis, ensuring accuracy and consistency.
- Analyze complex datasets while adhering to governance, security, and quality standards throughout the entire data life cycle, from collection to reporting.
- Apply basic statistical methods to interpret data trends, measure variability, and support evidence-based decision-making.
- Mine data efficiently to identify patterns, correlations, and actionable insights that drive business strategy and problem-solving.
- Understand data integration methods and how to combine multiple data sources for comprehensive analysis.
- Support data-driven decision-making by leveraging analytical tools and techniques to generate insights that inform business strategy.
Kursvoraussetzungen
- To enroll in the CompTIA Data+ course, learners should ideally have 18 to 24 months of experience in a report or business analyst role, where they have been actively involved in gathering, analyzing, and interpreting data to support business decision-making. Familiarity with databases and analytics tools is important, as these will be used throughout the course for practical exercises and real-world scenarios. A basic understanding of statistics, including concepts such as mean, median, standard deviation, and probability, is recommended to effectively apply analytical methods. Additionally, experience with data visualization tools or techniques is beneficial, as the course emphasizes presenting data insights clearly and effectively. Strong analytical thinking skills, attention to detail, and a curiosity for uncovering patterns in data will help learners succeed in the program. Prior exposure to spreadsheet software (like Excel) or business intelligence platforms is also advantageous but not mandatory.
Kursplan
| Datum | Tage übrig | Schulungsort | |
|---|---|---|---|
Keine Termine verfügbar | |||
Kursprüfungsinformationen
- CompTIA
Data+ is an entry- to early-career certification designed for professionals who
are beginning their journey in data analytics or looking to validate
foundational data skills. The certification demonstrates a candidate’s ability
to mine, analyze, and interpret data to inform business decision-making.
CompTIA Data+ emphasizes understanding data concepts, different data
environments, data collection and mining techniques, data visualization, basic
statistical methods, and data governance. The certification ensures that
professionals can effectively translate business requirements into actionable
insights and meaningful analyses. Being vendor-neutral, Data+ equips candidates
with transferable skills suitable for roles such as junior data analysts,
business intelligence specialists, reporting analysts, or any position that
requires working with structured and semi-structured data.
- Eligibility
/ Prerequisites:
While there are no mandatory prerequisites to take the Data+ exam, CompTIA recommends that candidates have approximately 18–24 months of experience in a reporting or business analyst role. Exposure to databases, data manipulation tools, analytical platforms, basic statistics, and visualization techniques is highly beneficial. This prior experience helps candidates grasp exam concepts more effectively. However, motivated newcomers to data analytics can also pursue Data+ successfully by combining study materials, hands-on practice, and exam preparation courses. The certification is designed to be accessible yet challenging enough to establish a solid data foundation.
- Exam
Structure:
The CompTIA Data+ certification is assessed through a single exam, DA0-001, which consists of up to 90 questions, including multiple-choice questions and a limited number of performance-based items (simulated, interactive scenarios). Candidates have 90 minutes to complete the exam. The passing score is 675 on a scale of 100–900. The exam covers five main domains:
- Data Concepts – foundational understanding of types of data, data structures, and the role of data in business.
- Data Environments – exposure to relational and non-relational databases, cloud and on-premises data storage, and data lifecycle management.
- Data Mining – techniques for collecting, cleaning, transforming, and profiling data to prepare it for analysis.
- Data Analysis and Visualization – applying descriptive statistics, summarizing data insights, creating dashboards, and interpreting results to inform decisions.
- Data Governance – understanding policies, procedures, compliance, data quality, and security standards that ensure reliable and ethical data usage.
- Renewal
/ Recertification:
The CompTIA Data+ certification is valid for three years from the date of issue. To maintain the credential, certified professionals must earn 20 Continuing Education Units (CEUs) over the three-year period or recertify through other qualifying CompTIA activities, such as completing a higher-tier certification or participating in relevant training programs. Data+ can automatically renew related lower-tier certifications like ITF+, if held. Failure to complete the renewal process results in expiration, as the certification is part of CompTIA’s Continuing Education Program, which encourages ongoing learning and skills maintenance.
- Additional
Notes:
Data+ not only validates technical data skills but also prepares candidates to communicate insights effectively to business stakeholders, ensuring that data-driven decision-making is accurate, actionable, and aligned with organizational goals. Its vendor-neutral approach makes it a flexible foundation for further certifications in analytics, data science, or business intelligence.
Bewertungen unserer Kunden
4.8
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Excellent
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Matthew Harris
I work with data every day, but I never really understood how much went into keeping it secure and useful. This course broke it down in a way that was actually engaging. I can see why iExperts puts so much emphasis on this.
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Daniel Anderson
Thank you for the training you provided. It was full of information that is useful and you were very good at delivering it. Hope to keep in touch,
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Dieser Kurs beinhaltet
- Dauer40 Std.
- AnbieterCompTIA
- KategorieData
- ZertifikatJa
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