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Passing Score, Duration & Questions For The CompTIA DA0-001 Exam
- Exam Length: 90 questions
- The passing score: 675 (on scale of 100-900)
- Time Duration: 90 minutes
- Format: Multiple choice and performance-based
- Languages: English
Things You Should Know about the CompTIA DA0-001 Exam
CompTIA Data+ is a certification that validates your understanding of the fundamentals of computer data storage and management. It's a foundational certification that can be used to secure entry-level positions in various fields, such as IT, business intelligence, and application development.
CompTIA Data+ is not the only certification available for this subject matter. The CompTIA A+ and Microsoft Certified Solutions Associate exams also cover similar material. However, unlike those exams, CompTIA D+ does not have a pre-requisite requirement for passing it. If you already have a working knowledge of networking, operating systems (OS), and some basic computer concepts, you can prepare for this exam without any prior experience in these areas. CompTIA DA0-001 exam dumps will help you to clear the concepts.
CompTIA Data+ is designed to ensure that candidates have a thorough understanding of how data storage works and the basic concepts involved in managing it. This includes an understanding of how information is stored electronically on hard drives, solid-state drives (SSDs), magnetic tapes, optical discs and other storage devices; along with how data can be retrieved from these devices using appropriate software tools.
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What is the exam cost of the CompTIA DA0-001 Exam
The exam cost of the CompTIA DA0-001 Exam is 239 USD.
Reference: https://www.comptia.org/training/books/data-da0-001-study-guide
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CompTIA DA0-001 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Visualization and Reporting | 23% | - Selecting appropriate visualizations and charts - Building dashboards and reports - Design principles and best practices - Communicating insights and recommendations |
| Topic 2: Data Analysis | 23% | - Interpreting results and identifying patterns/anomalies - Descriptive and inferential statistics - Statistical methods: correlation, regression, hypothesis testing - Analytical techniques: trend, performance, exploratory, comparative |
| Topic 3: 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 |
| Topic 4: Data Governance, Quality and Controls | 14% | - Data lifecycle management and controls - Data quality standards and measurement - Data privacy, security, and compliance - Data governance frameworks and policies |
| Topic 5: Data Mining | 25% | - Data acquisition and integration methods - Data transformation, manipulation, and enrichment - Querying and retrieving data - Data profiling, cleansing, and validation |
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