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Objectives of CompTIA DA0-001 Exam
In this section, we will list the objectives you should know in order to pass your CompTIA Data+ certification exam.
The first objective is to understand how to become a successful IT professional with data skills.
The second objective is to learn about different types of data, including structured and unstructured data.
The third objective is to be able to demonstrate your knowledge of at least two types of data storage: online and offline.
The fourth objective is to be able to describe how a client can access information from various sources through technology such as social media or the web. CompTIA DA0-001 exam dumps he best way to prepare for the exams.
The fifth objective is for you to be able to apply concepts related to using software applications such as Microsoft Office suite, Google Docs, and Adobe Creative Cloud.
Reference: https://www.comptia.org/training/books/data-da0-001-study-guide
Passing Score, Duration & Questions For The CompTIA DA0-001 Exam
- Languages: English
- Time Duration: 90 minutes
- Exam Length: 90 questions
- The passing score: 675 (on scale of 100-900)
- Format: Multiple choice and performance-based
CompTIA DA0-001 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Visualization and Reporting | 23% | - Design principles and best practices - Communicating insights and recommendations - Building dashboards and reports - Selecting appropriate visualizations and charts |
| Topic 2: Data Mining | 25% | - Data acquisition and integration methods - Data transformation, manipulation, and enrichment - Querying and retrieving data - Data profiling, cleansing, and validation |
| Topic 3: Data Analysis | 23% | - Descriptive and inferential statistics - Statistical methods: correlation, regression, hypothesis testing - Interpreting results and identifying patterns/anomalies - Analytical techniques: trend, performance, exploratory, comparative |
| Topic 4: Data Governance, Quality and Controls | 14% | - Data lifecycle management and controls - Data quality standards and measurement - Data governance frameworks and policies - Data privacy, security, and compliance |
| Topic 5: Data Concepts and Environments | 15% | - Data storage systems: databases, data marts, warehouses, data lakes - Structured, semi-structured, and unstructured data - Data types, structures, and formats - Data schemas, dimensions, and attributes |
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