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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Analysis | 23% | - Given a scenario, apply the appropriate descriptive statistical methods - Explain the purpose of inferential statistical methods - Summarize types of analysis and key analysis techniques |
| Topic 2: Data Concepts and Environments | 15% | - Identify basic concepts of data schemas and dimensions - Compare and contrast common data structures and file formats - Compare and contrast different data types |
| Topic 3: Data Governance, Quality, and Controls | 14% | - Explain key aspects of data quality - Summarize important data governance concepts - Compare and contrast types of data controls |
| Topic 4: Visualization | 23% | - Given a scenario, translate business requirements to support data-driven decisions - Given a scenario, apply the appropriate type of visualization - Given a scenario, use appropriate methods for dashboard development - Explain important aspects of a report that tell a data story - Compare and contrast types of reports |
| Topic 5: Data Mining | 25% | - Explain common techniques for data manipulation and optimization - Identify common reasons for cleansing and profiling datasets - Given a scenario, execute techniques for data manipulation - Explain data acquisition concepts |
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問題 #65
Which of the following would be considered non-personally identifiable information?
答案：D
解題說明：
Non-personally identifiable information (non-PII) is any data that cannot be used to identify, contact, or locate a specific individual, either alone or combined with other sources. Non-PII can include aggregated statistics, anonymous data, device identifiers, IP addresses, cookies, and other types of information that do not reveal the identity or location of a person. Cell phone device name is an example of non-PII, as it does not reveal any personal information about the owner or user of the device. Therefore, the correct answer is A. Reference: What is Non-Personally Identifiable Information (Non-PII)? | Definition and Examples, What is Personally Identifiable Information (PII)? | Definition and Examples
問題 #66
An analyst is working for an organization that has a vast amount of data stored across various systems and databases. Employees have difficulty locating and understanding the currently available data assets. Which of the following tools should the analyst implement to best solve this issue?
答案：B
解題說明：
A data catalog is specifically designed to help users:
* Discover what data assets exist across the organization.
* See metadata: table/field names, locations, owners, lineage, and usage.
* Often search by keyword, tag, or business term.
* Understand context, such as descriptions, classifications, and quality indicators.
This directly addresses the problem: employees have difficulty locating and understanding the current data assets.
Why other options are less suitable:
* Data lake (A) - is a storage repository for large volumes of raw/varied data; it does not, by itself, solve discoverability and understanding.
* Business glossary (B) - defines business terms and concepts (what "customer," "order," etc., mean), but does not by itself index all technical data assets and where they live.
* Operational data store (D) - is used for integrated operational reporting, not as a metadata-driven search and discovery tool.
Thus, the best tool to solve locating and understanding data assets is a Data catalog (C).
CompTIA Data+ Reference (concept alignment):
* DA0-001 Objectives - Data governance: tools such as data catalogs and business glossaries.
* Study content explaining that a data catalog indexes and documents data assets and supports discoverability.
問題 #67
A collections manager has a team calling customers who are past due on their accounts in an attempt to collect payments. The manager receives the call list in the form of a printed report that is generated by the accounting department at the beginning of each week. Consequently, the collections team calls some customers who have made payments in the time since the report was last printed. Which of the following reporting enhancements could the accounting department implement to best reduce the number of calls on current accounts?
答案：C
解題說明：
The best reporting enhancement that the accounting department could implement to reduce the number of calls on current accounts is C. Increase the frequency of report generation.
By increasing the frequency of report generation, the accounting department could provide the collections manager with more up-to-date information on the customers who are past due on their accounts. This would help to avoid calling customers who have made payments in the time since the last report was printed, and thus reduce the number of calls on current accounts. Increasing the frequency of report generation would also improve the accuracy and timeliness of the data, and enhance the efficiency and effectiveness of the collections process.
Modifying the date range on the report, including a time stamp on the report, or adding a report run date to the report would not be sufficient to reduce the number of calls on current accounts. These enhancements would only provide information on when the report was generated or what period it covers, but they would not change the fact that the report could be outdated by the time it reaches the collections manager. Therefore, these enhancements would not solve the problem of calling customers who have already paid their accounts.
問題 #68
You are measuring how much a child has grown over the past year and would like to express that using a percentage.
What calculation is most appropriate?
答案：D
問題 #69
Which of the following should be accomplished NEXT after understanding a business requirement for a data analysis report?
答案：C
解題說明：
Exploratory data analysis (EDA) is a process of examining and summarizing a dataset using various techniques, such as descriptive statistics, visualizations, correlations, outliers detection, and hypothesis testing. EDA can help reveal the main characteristics, patterns, trends, and insights from the data, as well as identify any problems or issues with the data quality or structure. EDA is usually performed after understanding a business requirement for a data analysis report and before building a mock dashboard
/presentation layout. Therefore, the correct answer is B. References: [What is Exploratory Data Analysis? | Definition and Examples], [Exploratory Data Analysis in Python]
問題 #70
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