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| Topic | Details |
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| Topic 1 | - 5.0 Data Governance, Quality, and Controls
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| Topic 2 | - Visualization: This section of the exam measures skills of a Data Visualisation Specialist and focuses on turning raw data into clear, visual insights. It teaches how to match visual formats like bar charts, heat maps, and line graphs to specific audiences and needs. Candidates must understand how to create dashboards and reports using proper design elements such as labels, layout, branding, and colour schemes. This section also includes best practices for dashboard development and delivery through various platforms and user access levels.
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| Topic 3 | - This section of the exam measures skills of a Data Governance Associate and introduces principles for keeping data secure, accurate, and compliant. It covers access controls, encryption, classification of sensitive data like PII and PHI, and legal requirements tied to data use. Candidates must know how to apply quality checks, validate data, and manage master data effectively. It also addresses best practices for maintaining integrity through data dictionaries, audits, and standardisation processes.
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| Topic 4 | - Data Concepts and Environments: This section of the exam measures the skills of a Junior Data Analyst and focuses on understanding core data concepts such as database types, schema structures, and data formats. It highlights differences between structured and unstructured data, compares file types like CSV, JSON, and XML, and introduces key ideas about data dimensions and slowly changing dimensions. Knowing how data is stored and organized helps professionals better prepare for analysis and reporting tasks.
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| Topic 5 | - Data Analysis: This section of the exam measures skills of a Reporting Analyst and includes foundational knowledge of statistical methods such as averages, variances, and standard deviation. It covers how to use data to find patterns, track performance, and make predictions. This domain also introduces hypothesis testing, regression, correlation, and different types of analysis like exploratory and trend analysis. Candidates should also be aware of common tools used for analysis, including Excel, SQL, Python, R, and popular BI platforms like Tableau and Power BI.
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CompTIA Data+ Exam Sample Questions (Q181-Q186):
NEW QUESTION # 181
A data analyst is designing a report for the business review team. The team lists the following requirements for the report:
* Specific data points
* Color branding
* Labels and terminology
* Suggested charts and tables
Which of the following components is missing from the requirements?
- A. Report type
- B. Source validation
- C. Delivery method
- D. Design elements
Answer: C
Explanation:
This question falls under theVisualization and Reportingdomain of CompTIA Data+ DA0-002, which involves understanding the components necessary for designing a report. The given requirements cover data, visuals, and design, but a key aspect of report planning is missing.
* Source validation (Option A): Source validation ensures data accuracy, but it's typically part of the data preparation phase, not a report design requirement.
* Design elements (Option B): Color branding, labels, and terminology are design elements, so this is already included.
* Delivery method (Option C): The delivery method (e.g., recurring, ad hoc, self-service) specifies how the report will be distributed or accessed, which is a critical requirement missing from the list.
* Report type (Option D): Suggested charts and tables imply the report type (e.g., summary, dashboard), so this is indirectly covered.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and the delivery method is a key component of report planning that's missing here.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.
NEW QUESTION # 182
A data analyst needs to join data from two tables in a way that all data from one table is shown even if a matching row is not in the other table. Which of the following should the analyst use to achieve the desired output?
- A. CROSS JOIN
- B. FULL OUTER JOIN
- C. RIGHT OUTER JOIN
- D. INNER JOIN
Answer: C
Explanation:
A right outer join returns all records from one table while including matching records from the other table when available, ensuring all data from the specified table is preserved even without matches.
NEW QUESTION # 183
Which of the following report types is considered the most important in a legal and compliance context?
- A. Operational
- B. Regulatory
- C. Performance
- D. Investment
Answer: B
Explanation:
Regulatory reports are critical in legal and compliance contexts because they ensure adherence to laws, regulations, and standards.
NEW QUESTION # 184
A data analyst is creating a new dataset that involves bringing together the following datasets:

Which of the following would be the output if the data analyst does a FULL JOIN?
Answer: C
Explanation:
A FULL JOIN returns all records from both tables. Matching records are combined based on the common ID field, while nonmatching records from either table are still included with null or blank values for the missing columns.
In the source data:
ID 23525 exists in both tables, so Frank is combined with the Chicago address.
ID 11290 exists in both tables, so Martha is combined with the Miami address.
ID 12141 exists only in the first table, so Ellen appears with blank address information.
ID 11040 exists only in the second table, so the address record appears with blank name and date-of-birth information.
NEW QUESTION # 185
Which of the following elements is the most important to include in a dashboard for internal technical audiences?
- A. Dynamic features
- B. Key performance indicators
- C. Methodology section
- D. Company branding
Answer: B
NEW QUESTION # 186
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