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Last Updated: Aug 22, 2026
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Introduction of CompTIA DA0-001 Exam
The CompTIA Data+ certification is a vendor neutral certification that validates the ability to use data to solve business problems. It is designed for professionals who work with or support IT, including IT manager, analyst, consultant and project manager.
CompTIA Data+ is focused on the skills necessary to analyze, manage and implement information technology systems within an organization. The exam covers how to collect and analyze data using tools such as spreadsheets and databases; how to use this data to make informed decisions about IT projects; how to create reports from the data; how to communicate findings clearly and concisely through presentations and reports; how to identify security issues related to information assets; and how to apply appropriate standards for data management practices across your company or organization. CompTIA DA0-001 exam dumps are the best practice exams.
The CompTIA Data+ certification is designed for professionals working in a variety of fields such as finance, marketing, human resources, sales and legal who use data in their jobs. The manipulation of the schedule programming dimensions driven updates role components activity interface busy campaigns advertising reasons activities with decision news.
Reference: https://www.comptia.org/training/books/data-da0-001-study-guide
What is the exam cost of the CompTIA DA0-001 Exam
The exam cost of the CompTIA DA0-001 Exam is 239 USD.
Passing Score, Duration & Questions For The CompTIA DA0-001 Exam
- Languages: English
- Format: Multiple choice and performance-based
- Exam Length: 90 questions
- Time Duration: 90 minutes
- The passing score: 675 (on scale of 100-900)
CompTIA DA0-001日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Visualization and Reporting | 23% | - Selecting appropriate visualizations and charts - Building dashboards and reports - Communicating insights and recommendations - Design principles and best practices |
| Data Mining | 25% | - Data profiling, cleansing, and validation - Data transformation, manipulation, and enrichment - Data acquisition and integration methods - Querying and retrieving data |
| Data Governance, Quality and Controls | 14% | - Data privacy, security, and compliance - Data quality standards and measurement - Data governance frameworks and policies - Data lifecycle management and controls |
| Data Concepts and Environments | 15% | - Data types, structures, and formats - Data schemas, dimensions, and attributes - Structured, semi-structured, and unstructured data - Data storage systems: databases, data marts, warehouses, data lakes |
| Data Analysis | 23% | - Analytical techniques: trend, performance, exploratory, comparative - Interpreting results and identifying patterns/anomalies - Statistical methods: correlation, regression, hypothesis testing - Descriptive and inferential statistics |
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