PDF Version DemoPassing Score, Duration & Questions For The CompTIA DA0-001 Exam
- Format: Multiple choice and performance-based
- Languages: English
- The passing score: 675 (on scale of 100-900)
- Time Duration: 90 minutes
- Exam Length: 90 questions
Reference: https://www.comptia.org/training/books/data-da0-001-study-guide
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Understanding CompTIA DA0-001 Exam Topics
Applying basic statistical methods
Manipulating data
Mining data
Visualizing and reporting data
Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle
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What is the salary of the CompTIA DA0-001 Exam
The Average salary of different countries for CompTIA DA0-001 professionals:
- India: INR 4293726 per year
- United States: USD 55,000 per year
- United Kingdom: Pound 45489
What are the special features of the CompTIA DA0-001 Exam
The CompTIA Data+ certification is an important one, because it's the first of its kind. It was developed to ensure that IT professionals had the necessary skills to work with data and perform advanced analysis.
The CompTIA Data+ certification is also unique in that it can be applied across several different industries. In fact, the curriculum for this exam focuses on three different areas: data analysis, communication and technology. This means that you'll need a strong understanding of all three areas to qualify for this exam. CompTIA DA0-001 exam dumps are the best way to make you perp fast.
The CompTIA Data+ certification is designed for those who have already gained experience working with data or those who want to learn more about it. The test consists of a series of questions designed to measure your knowledge about various aspects of data analysis.
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CompTIA DA0-001 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Visualization | 23% | - Given a scenario, apply the appropriate type of visualization - Given a scenario, use appropriate methods for dashboard development - Compare and contrast types of reports - Explain important aspects of a report that tell a data story - Given a scenario, translate business requirements to support data-driven decisions |
| Data Mining | 25% | - Explain data acquisition concepts - Explain common techniques for data manipulation and optimization - Given a scenario, execute techniques for data manipulation - Identify common reasons for cleansing and profiling datasets |
| Data Analysis | 23% | - Summarize types of analysis and key analysis techniques - Explain the purpose of inferential statistical methods - Given a scenario, apply the appropriate descriptive statistical methods |
| Data Governance, Quality, and Controls | 14% | - Explain key aspects of data quality - Summarize important data governance concepts - Compare and contrast types of data controls |
| Data Concepts and Environments | 15% | - Compare and contrast common data structures and file formats - Compare and contrast different data types - Identify basic concepts of data schemas and dimensions |
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