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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Analysis | 25% | - Statistical methods and analysis techniques - Data interpretation and reporting - Trend and pattern identification |
| Topic 2: Data Governance, Quality, and Controls | 15% | - Compliance, privacy, and security controls - Data quality management - Data governance frameworks and policies |
| Topic 3: Data Mining | 25% | - Data collection and extraction methods - Data processing and transformation - Data manipulation and cleaning techniques |
| Topic 4: Data Concepts and Environments | 15% | - Data lifecycle and data ecosystems - Data storage systems and platforms - Data types, structures, and file formats |
| Topic 5: Visualization | 20% | - Visualization best practices - Chart and dashboard design principles - Data storytelling and reporting tools |
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質問 # 136
A product goes viral on social media, creating high demand. Distribution channels are facing supply chain issues because the testing and training models that are used for sales forecasting have not encountered similar demand. Which of the following best describes this situation?
正解：A
解説：
This question pertains to theData Analysisdomain, focusing on issues with forecasting models. The scenario describes a sudden change in demand (viral product) that the model couldn't predict because it hasn't seen similar patterns before.
* Model bias (Option A): Model bias occurs when a model systematically favors certain outcomes due to flawed training data, but this scenario is about a change in data patterns, not bias.
* Data drift (Option B): Data drift occurs when the statistical properties of the data change over time (e.
g., sudden high demand due to virality), causing the model to perform poorly because it was trained on different patterns, which fits the scenario.
* Incorrect sizing (Option C): This term is vague and not a standard concept in data analysis for this context.
* Skewing (Option D): Skewing refers to data distribution asymmetry, not a change in data patterns affecting model performance.
The DA0-002 Data Analysis domain includes understanding "applying the appropriate descriptive statistical methods," and data drift is a key concept in forecasting when data patterns change unexpectedly.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
質問 # 137
A data analyst created a dashboard to illustrate the traffic volume and mean response time for a call center. The traffic data is current, but the mean response time has not updated for more than an hour. Which of the following is the best way to verify the data's freshness?
正解：A
解説：
Checking when the calculation script last ran verifies whether the metric is being refreshed properly, which directly confirms the data's freshness.
質問 # 138
A project manager requests an unscheduled report that provides a list of clients. Which of the following frequencies is best for this report?
正解：C
解説：
An ad hoc report is created on demand to satisfy a specific, unscheduled request. Since the project manager requested a report outside the regular reporting schedule, an ad hoc report is the most appropriate choice.
質問 # 139
Given the following table:
ID
Value
1
1.5
2
24.456
3
113
Which of the following data types should an analyst use for the numeric values in the Value column?
正解：A
解説：
This question falls under theData Concepts and Environmentsdomain of CompTIA Data+ DA0-002, focusing on selecting appropriate data types for a given dataset. The Value column contains decimal numbers (1.5, 24.456, 113), requiring a data type that supports such values.
* Double (Option A): Double is a floating-point data type that supports decimals with higher precision than Float, but it's often overkill for typical datasets unless very high precision is needed, which isn't indicated here.
* Float (Option B): Float is a floating-point data type that supports decimal numbers (e.g., 1.5, 24.456) and is commonly used for such values in databases, making it the best choice.
* Boolean (Option C): Boolean is for true/false values, not numeric data.
* Integer (Option D): Integer is for whole numbers, but the values (e.g., 1.5, 24.456) have decimals, so Integer is not suitable.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," such as selecting data types like Float for decimal numeric values.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.
質問 # 140
Which of the following data repositories stores unaltered data?
正解：B
解説：
A data lake stores raw, unaltered data in its native format, including structured, semi-structured, and unstructured data. This allows organizations to retain data as originally collected and transform it later when needed for analysis.
質問 # 141
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