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CompTIA Data+ Certification Exam Certification Sample Questions and Practice Exam
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CompTIA Data+ Certification Exam is a valuable certification for individuals who want to demonstrate their expertise in data management. CompTIA Data+ Certification Exam certification can help individuals stand out in the competitive job market and increase their earning potential. CompTIA Data+ Certification Exam certification is also a requirement for some job roles in the data management field, making it a must-have for individuals who want to advance their careers.
CompTIA Data+ Certification Exam Sample Questions (Q364-Q369):
NEW QUESTION # 364
A sales analyst needs to report how the sales team is performing to target. Which of the following files will be important in determining 2019 performance attainment?
- A. 2018 goal data
- B. 2019 commission plan
- C. 2018 actual revenue
- D. 2019 goal data
Answer: D
Explanation:
Answer : C . 2019 goal data
To report how the sales team is performing to target, the sales analyst needs to compare the actual sales revenue with the expected or planned sales revenue for the same period. The 2019 goal data is the file that contains the expected or planned sales revenue for the year 2019, which is the target that the sales team is aiming to achieve. By comparing the 2019 goal data with the 2019 actual revenue, the sales analyst can calculate the performance attainment, which is the percentage of the goal that was met by the sales team.
Option A is incorrect, as 2018 goal data is not relevant for determining 2019 performance attainment. The 2018 goal data contains the expected or planned sales revenue for the year 2018, which is not the target that the sales team is aiming to achieve in 2019.
Option B is incorrect, as 2018 actual revenue is not relevant for determining 2019 performance attainment. The 2018 actual revenue contains the actual sales revenue for the year 2018, which is not comparable with the 2019 goal data or the 2019 actual revenue.
Option D is incorrect, as 2019 commission plan is not relevant for determining 2019 performance attainment. The 2019 commission plan contains the rules and rates for calculating and paying commissions to the sales team based on their performance attainment, but it does not contain the expected or planned sales revenue for the year 2019.
NEW QUESTION # 365
Which of the following describes the use of a representative amount of data from a main repository?
- A. Sampling
- B. Web scraping
- C. Observation
- D. Delta load
Answer: A
Explanation:
Sampling refers to the process of selecting a representative subset of data from a larger data set or repository. This technique is used when it is impractical or unnecessary to analyze the entire set of data. A representative sample should accurately reflect the characteristics of the larger population, allowing for analysis and inference about the population as a whole12.
Observation (A) generally refers to the act of monitoring or recording data. Delta load (B) is a term used in data warehousing to describe the process of loading only the changes since the last data extraction, rather than the entire data set. Web scraping is the process of extracting data from websites.
Reference:
Understanding the importance of data sampling1.
The concept of a representative sample in statistics2.
Data repository management and usage3.
Benefits and methods of data sampling4.
NEW QUESTION # 366
Given the following graph:
Which of the following summary statements upholds integrity in data reporting?
- A. Sales are approximately equal for Product A and Product B across all strategies.
- B. While Strategy 2 does not result in the highest sales of Product D, over all products it appears to be the most effective.
- C. Strategy 4 provides the best sales in comparison to other strategies.
- D. Product D should be promoted more than the other products in all strategies.
Answer: C
Explanation:
Explanation
Strategy 4 provides the best sales in comparison to other strategies. This is because the total sales for Strategy
4 are the highest among all the strategies, as shown by the black line. The other statements are not accurate or do not uphold integrity in data reporting. Here is why:
Statement A is false because sales are not approximately equal for Product A and Product B across all strategies. For example, in Strategy 1, Product A has more sales than Product B, while in Strategy 3, Product B has more sales than Product A.
Statement C is misleading because it does not account for the difference in scale between the products. While Strategy 2 has the highest total sales among all products, it does not necessarily mean that it is the most effective for each product. For instance, Product D has very low sales in Strategy 2 compared to other strategies.
Statement D is biased because it does not provide any evidence or justification for why Product D should be promoted more than the other products in all strategies. It also ignores the fact that Product D has the lowest sales among all products in most of the strategies.
NEW QUESTION # 367
An analyst has generated a report that includes the number of months in the first two quarters of 2019 when sales exceeded $50,000:
Which of the following functions did the analyst use to generate the data in the Sales_indicator column?
- A. Sort
- B. Logical
- C. Date
- D. Aggregate
Answer: D
NEW QUESTION # 368
A data analyst must separate the column shown below into multiple columns for each component of the name:
Which of the following data manipulation techniques should the analyst perform?
- A. Concatenating
- B. Parsing
- C. Imputing
- D. Transposing
Answer: B
Explanation:
Explanation
Parsing is the data manipulation technique that should be used to separate the column into multiple columns for each component of the name. Parsing is the process of breaking down a string of text into smaller units, such as words, symbols, or numbers. Parsing can be used to extract specific information from a text column, such as names, addresses, phone numbers, etc. Parsing can also be used to split a text column into multiple columns based on a delimiter, such as a comma, space, or dash1. In this case, the analyst can use parsing to split the column by the comma delimiter and create three new columns: one for the last name, one for the first name, and one for the middle initial. This will make the data more organized and easier to analyze.
NEW QUESTION # 369
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