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| Section | Weight | Objectives |
|---|---|---|
| Data Concepts and Environments | 20% | - Cloud and distributed data environments - Foundational concepts of AI and machine learning in data - Data types, structures, and formats - Database systems and architectures |
| Data Analysis | 24% | - Statistical methods and techniques - Exploratory and confirmatory data analysis - Data modeling and pattern recognition - Analytical tools and querying languages |
| Data Governance, Quality, and Management | 14% | - Data governance frameworks and policies - Data lifecycle management and documentation - Data privacy, security, and compliance - Data quality standards and monitoring |
| Visualization and Reporting | 20% | - Dashboard and report development - Validation and accuracy of reports - Communicating insights to stakeholders - Design principles for effective visualizations |
| Data Acquisition and Preparation | 22% | - Data collection methods and sources - Data extraction, transformation, and loading (ETL/ELT) - Data integration and normalization - Data cleaning, validation, and quality improvement |
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NEW QUESTION # 81
An analyst is recording the following financial transaction data with a vendor:
59.99, 49.50, 70.49
Which of the following data types is the best way to record this information?
Answer: D
Explanation:
Currency data type is specifically designed to store monetary values with appropriate precision and formatting for financial transactions.
NEW QUESTION # 82
A data analyst is creating a high-level report for the Chief Executive Officer. Which of the following data would most likely be included in the report?
Answer: B
Explanation:
Year-to-date sales numbers provide high-level performance insights appropriate for executive decision-making.
NEW QUESTION # 83
A sales manager wants to understand how sales are trending year over year. Which of the following chart types is the most appropriate to display the information?
Answer: B
NEW QUESTION # 84
A data analyst is following up on a recent, company-wide data audit of customer invoice data. Which of the following is the best option for the analyst to use?
Answer: A
Explanation:
This question falls under theData Governancedomain of CompTIA Data+ DA0-002, which includes understanding compliance frameworks for data audits, especially for customer data. The scenario involves a data audit of customer invoice data, which likely contains personal information, making privacy regulations relevant.
* PCI DSS (Option A): PCI DSS (Payment Card Industry Data Security Standard) applies specifically to payment card data, not general customer invoice data unless credit card details are involved, which isn't specified.
* GDPR (Option B): GDPR (General Data Protection Regulation) is a comprehensive privacy regulation for handling personal data of EU citizens, including customer invoice data, which may contain PII like names and addresses. It's the most relevant for a company-wide data audit.
* ISO (Option C): ISO standards (e.g., ISO 27001) relate to information security management but are not specific to customer data privacy audits.
* PII (Option D): PII (Personally Identifiable Information) is a concept, not a framework or tool for conducting an audit.
The DA0-002 Data Governance domain emphasizes "identifying PII and data privacy concepts," and GDPR is the most appropriate framework for auditing customer data to ensure compliance with privacy laws.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.
NEW QUESTION # 85
Giving the following values:
47
59
83
33
51
39
52
Which of the following is the mean?
Answer: C
Explanation:
The mean is the average of the values: (47 + 59 + 83 + 33 + 51 + 39 + 52) ÷ 7 = 51.43, rounded to 51.
NEW QUESTION # 86
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