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질문 # 59
A data analyst receives a notification that a customized report is taking too long to load. After reviewing the system, the analyst does not find technical or operational issues. Which of the following should the analyst try next?
정답：D
설명：
This question pertains to theData Governancedomain, focusing on data quality and report performance optimization. The report is slow despite no technical issues, suggesting a data-related inefficiency.
* Check that the appropriate filters are applied (Option A): Applying filters reduces the dataset size by excluding irrelevant data, improving report performance. This is a logical next step after ruling out technical issues.
* Check data source connections (Option B): The analyst already reviewed the system and found no operational issues, so connectivity is likely not the problem.
* Check for data structure changes in the report (Option C): While possible, this is a deeper investigation step and less likely to be the immediate cause of slowness.
* Check whether other peers have the same issue (Option D): This might confirm the issue's scope but doesn't directly address the performance problem.
The DA0-002 Data Governance domain emphasizes "data quality control concepts," including optimizing report performance through techniques like filtering.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.
질문 # 60
Which of the following best describes the purpose of a primary key?
정답：C
설명：
A primary key uniquely identifies each row in a table. It ensures that every record can be distinguished from all others and prevents duplicate entries for the key field, maintaining data integrity within the table.
질문 # 61
Which of the following allows a data analyst to send out a spreadsheet containing sensitive information without revealing personal details?
정답：A
설명：
This question pertains to theData Governancedomain, focusing on data privacy and security. The task is to share a spreadsheet with sensitive information while protecting personal details.
* Using a UUID in the data file (Option A): A UUID (Universally Unique Identifier) can anonymize records, but if other PII (e.g., names) remains, personal details are still exposed.
* Redacting all PII (Option B): Redacting personally identifiable information (PII) removes sensitive details (e.g., names, addresses), ensuring personal information isn't revealed while sharing the spreadsheet.
* Adding access controls to the ID column (Option C): Access controls limit who can view the data, but the question focuses on the spreadsheet content itself, not access.
* Encrypting the spreadsheet (Option D): Encryption protects the file during transmission, but once opened, personal details are still visible unless redacted.
The DA0-002 Data Governance domain includes "data privacy concepts," and redacting PII is the most direct method to protect personal details in a shared spreadsheet.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.
질문 # 62
A data analyst is designing a report for a grocery chain and needs to include stores, product placement, and SKUs. Which of the following best describes the data management concept that the analyst is considering?
정답：C
설명：
Hierarchy describes the organization of data into levels or parent-child relationships. In this case, stores, product placement, and SKUs represent related levels within a structured business hierarchy, allowing the analyst to organize and report data according to those relationships.
질문 # 63
A data analyst receives a flat file that includes dates. The analyst needs to calculate the number of days from the dates on the file to the current date. Which of the following is the best way to complete this task?
정답：A
설명：
This question pertains to theData Analysisdomain, focusing on date calculations. The task is to calculate the difference between dates in a file and the current date, requiring proper date handling.
* Convert data to date format and use date functions (Option A): Flat files often store dates as strings (e.g., "2023-01-01"). Converting them to a date format (e.g., using Python's datetime or SQL's TO_DATE) allows the use of date functions (e.g., DATEDIFF) to calculate the difference to the current date, which is the best approach.
* Validate the date format with logical functions and use date functions to analyze (Option B):
Validation is unnecessary if conversion handles format issues, making this overly complex.
* Use date functions to analyze the data with no conversion (Option C): Without converting to a date format, date functions may fail if the data is stored as strings.
* Transform data to a numerical value and use mathematical functions (Option D): This is inefficient and error-prone compared to using date functions.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and converting to date format followed by date functions is the standard method for such calculations.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
질문 # 64
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