Study CompTIA DA0-001 Materials | Valid DA0-001 Exam Syllabus
Study CompTIA DA0-001 Materials | Valid DA0-001 Exam Syllabus
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Study DA0-001 Materials and CompTIA Valid DA0-001 Exam Syllabus: CompTIA Data+ Certification Exam Exam Pass Once Try
New developments in the tech sector always bring new job opportunities. These new jobs have to be filled with the CompTIA Data+ Certification Exam (DA0-001) certification holders. So to fill the space, you need to pass the CompTIA Data+ Certification Exam (DA0-001) exam. Earning the CompTIA Data+ Certification Exam (DA0-001) certification helps you clear the obstacles you face while working in the CompTIA field. To get prepared for the CompTIA Data+ Certification Exam (DA0-001) certification exam, applicants face a lot of trouble if the study material is not updated.
CompTIA Data+ Certification Exam Sample Questions (Q181-Q186):
NEW QUESTION # 181
Which of the following is a control measure for preventing a data breach?
- A. Data retention
- B. Data encryption
- C. Data transmission
- D. Data attribution
Answer: B
Explanation:
This is because data encryption is a type of control measure that prevents a data breach, which is an unauthorized or illegal access or use of data by an external or internal party. Data encryption can prevent a data breach by protecting and securing the data using a code or a key that scrambles or transforms the data into an unreadable or incomprehensible format, which can only be decoded or restored by authorized users who have the correct code or key. For example, data encryption can prevent a data breach by encrypting the data in transit or at rest, such as when the data is sent over a network or stored in a device. The other control measures are not used for preventing a data breach. Here is why:
Data transmission is a type of process that transfers and exchanges data between different sources or systems, such as databases, cloud services, or web applications. Data transmission does not prevent a data breach, but rather exposes the data to potential risks or threats during the transfer or exchange. However, data transmission can be made more secure and less vulnerable to a data breach by using encryption or other methods, such as authentication or authorization.
Data attribution is a type of feature or function that assigns and tracks the ownership and origin of the data, such as the creator, modifier, or source of the data. Data attribution does not prevent a data breach but rather provides information and evidence about the data provenance and history. However, data attribution can be useful for detecting and responding to a data breach by using audit logs or metadata to identify and trace any unauthorized or illegal access or use of the data.
Data retention is a type of policy or standard that specifies and regulates the storage and preservation of the data, such as the duration, location, or format of the data. Data retention does not prevent a data breach, but rather affects the availability and accessibility of the data for future use or reference. However, data retention can be optimized and aligned with the legal and ethical requirements and standards of the industry or the organization to reduce the risk or impact of a data breach.
NEW QUESTION # 182
Which of the following is the first step an analyst should perform upon receiving a business request for analysis?
- A. Determine the data needs and sources for analysis.
- B. Finalize the methodology to solve the problem.
- C. Initiate the analysis for exploratory data analysis.
- D. Review the business questions to understand the scope.
Answer: D
Explanation:
C: Review the business questions to understand the scope.
The first step an analyst should perform upon receiving a business request for analysis is to review the business questions to understand the scope of the problem, the objectives, and the expected outcomes. This will help the analyst to define the analytical approach, identify the data needs and sources, and plan the analysis process. Reviewing the business questions will also help the analyst to communicate with the stakeholders and clarify any assumptions or ambiguities1.
Option A is incorrect, as determining the data needs and sources for analysis is not the first step, but rather a subsequent step that depends on the business questions and the analytical approach.
Option B is incorrect, as initiating the analysis for exploratory data analysis is not the first step, but rather a part of the analysis process that involves examining and summarizing the data, identifying patterns and outliers, and testing hypotheses.
Option D is incorrect, as finalizing the methodology to solve the problem is not the first step, but rather a later step that involves selecting and applying the appropriate analytical techniques, tools, and models to answer the business questions.
NEW QUESTION # 183
You are working with a dataset and want to change the names of categories that you used for different types of books.
What term best describes this action?
- A. Recording.
- B. Summarizing
- C. Filtering.
- D. Aggregating.
Answer: A
Explanation:
Explanation
The term that best describes the action of changing the names of categories that you used for different types of books is recoding. Recoding is a process of transforming or modifying the values of a variable or a category to make them more meaningful, consistent, or accurate. For example, you can recode the names of book genres from "Fiction", "Non-Fiction", "Biography", etc. to "FIC", "NF", "BIO", etc. to make them shorter and easier to use. Reference: Recoding Data - SPSS Tutorials - LibGuides at Kent State University
NEW QUESTION # 184
Refer to the exhibit.
Given the image below:
The data should be cleaned because of the presence of:
- A. multicollinearity.
- B. invalid data.
- C. non-parametric data.
- D. outlier
Answer: D
Explanation:
The answer is A. Outlier.
Short explanation: An outlier is a data point that differs significantly from the rest of the data in a dataset. An outlier can indicate an error, an anomaly, or a rare event in the data. An outlier can affect the statistical analysis and visualization of the data, such as skewing the mean, variance, or distribution of the data. Therefore, data should be cleaned to identify and remove or correct any outliers.
The image below shows a box plot graph with a vertical axis labeled "Customer Calls" and a horizontal axis labeled "Churn". The box plot is blue in color and the median value is around 2. There are 7 outliers above the box plot, ranging from 4 to 8.
image)
A box plot is a type of graph that can show the distribution of data values using five summary statistics: minimum, maximum, median, first quartile, and third quartile. The box represents the interquartile range (IQR), which is the difference between the first and third quartiles. The median is shown as a line inside the box. The whiskers extend from the box to the minimum and maximum values, excluding any outliers. Outliers are shown as dots or circles outside the whiskers.
In this graph, we can see that most of the customer calls are between 0 and 4, with a median of 2. However, there are 7 outliers that have more than 4 customer calls, up to 8. These outliers may indicate some customers who have more issues or complaints than others, or some errors or anomalies in the data collection or recording process. These outliers can affect the analysis and interpretation of the customer calls and churn relationship, such as making it seem that more customer calls lead to less churn, which may not be true for the majority of the customers. Therefore, data should be cleaned to investigate and handle these outliers appropriately.
NEW QUESTION # 185
How many variables may be shown in a simple pie chart?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: A
NEW QUESTION # 186
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