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CompTIA Data+ Certification Exam Sample Questions (Q109-Q114):

NEW QUESTION # 109
James wants to analyze profit based on sales of five different product categories.
His source data set consists of 5.8 million rows with columns including region, product category, product name, and sales price.
How should he manipulate the data to facilitate his analysis?
Choose the best answer.

A. Transpose by sales price and summarize.
B. Transpose by region and summarize.
C. Transpose by product category and summarize.
D. Transpose by product name and summarize.

Answer: C

Explanation:
Correct answer B. Transpose by product category and summarize.
We can transpose this data by product category to perform this analysis broken out by product category.
Transposing by sales price, region, or product name will not further his state analytical goal.

NEW QUESTION # 110
Given the following data set:

Which of the following is the best reason for cleansing the data?

A. Corrupt data
B. Imputed data
C. Redundant data
D. Duplicate data

Answer: D

Explanation:
Comprehensive and Detailed In-Depth Explanation:
In data management,duplicate datarefers to identical records that appear multiple times within a dataset. Such duplicates can lead to inaccurate analyses, inflated metrics, and erroneous business decisions. Identifying and removing duplicate records is a critical step in the data cleansing process to ensure data quality and reliability.
Option A:Duplicate data
* Rationale:The dataset shows that the record with ID 376, Amount $400, and SKU ABV-DYH appears twice. This repetition indicates the presence of duplicate data, which can skew analysis results if not addressed.
Option B:Imputed data
* Rationale:Imputed data refers to missing or incomplete data that has been estimated or filled in based on other available information. There is no evidence in the provided dataset to suggest that any data has been imputed.
Option C:Redundant data
* Rationale:Redundant data involves unnecessary repetition of data across different fields or tables, leading to inefficiencies. While duplicate data is a form of redundancy, in this context, the specific issue is the exact repetition of entire records, making "duplicate data" the more precise term.
Option D:Corrupt data
* Rationale:Corrupt data refers to data that has been altered or damaged, making it incorrect or unusable.
The dataset provided does not exhibit signs of corruption, such as garbled text or invalid formats.

NEW QUESTION # 111
Which of the following can be used to translate data into another form so it can only be read by a user who has a key or a password?

A. Data transmission.
B. Data protection.
C. Data encryption.
D. Data masking.

Answer: C

Explanation:
Explanation
Data encryption can be used to translate data into another form so it can only be read by a user who has a key or a password. Data encryption is a process of transforming data using an algorithm or a cipher to make it unreadable to anyone except those who have the key or the password to decrypt it. Data encryption is a common method of protecting data from unauthorized access, modification, or theft. Reference: Guide to CompTIA Data+ and Practice Questions - Pass Your Cert

NEW QUESTION # 112
Given the below:

Which of the following numbers represents a Type I error?

A. 0
B. 1
C. 2
D. 3

Answer: B

NEW QUESTION # 113
A user receives a large custom report to track company sales across various date ranges. The user then completes a series of manual calculations for each date range. Which of the following should an analyst suggest so the user has a dynamic, seamless experience?

A. Add macros to the report to speed up the filtering and calculations process.
B. Create multiple reports, one for each needed date range.
C. Build calculations into the report so they are done automatically.
D. Create a dashboard with a date range picker and calculations built in.

Answer: D

Explanation:
Create a dashboard with a date range picker and calculations built in. This is because a dashboard is a type of visualization that displays multiple charts or graphs on a single page, usually to provide an overview or summary of some data or information. A dashboard can be used to track company sales across various date ranges by showing different metrics and indicators related to sales, such as revenue, volume, or growth. By creating a dashboard with a date range picker and calculations built in, the analyst can suggest a way for the user to have a dynamic, seamless experience, which means that the user can interact with and customize the dashboard according to their needs or preferences, as well as avoid any manual work or errors. For example, a date range picker is a type of feature or function that allows users to select or adjust the time period for which they want to see the data on the dashboard, such as daily, weekly, monthly, or quarterly. A date range picker can make the dashboard dynamic, as it can automatically update or refresh the dashboard with new data based on the selected time period. Calculations are mathematical operations or expressions that can be performed on the data on the dashboard, such as addition, subtraction, multiplication, division, average, sum, etc.
Calculations can make the dashboard seamless, as they can eliminate the need for manual calculations for each date range, as well as ensure accuracy and consistency of the results. The other ways are not the best ways to provide a dynamic, seamless experience for the user. Here is why:
* Creating multiple reports, one for each needed date range would not provide a dynamic, seamless experience for the user, but rather create a static, cumbersome experience, which means that the user cannot interact with or customize the reports according to their needs or preferences, as well as have to deal with multiple files or pages. For example, creating multiple reports would make it difficult for the user to compare or contrast the sales across different date ranges, as well as increase the workload and complexity of managing and maintaining the reports.
* Building calculations into the report so they are done automatically would not provide a dynamic, seamless experience for the user, but rather provide a partial, limited experience, which means that the user can only benefit from one aspect or feature of the report, but not from others. For example, building calculations into the report would help with avoiding manual work or errors, but it would not help with interacting with or customizing the report according to different date ranges.
* Adding macros to the report to speed up the filtering and calculations process would not provide a dynamic, seamless experience for the user, but rather provide an advanced, complex experience, which means that the user would need to have some technical skills or knowledge to use or apply the macros, as well as face some potential risks or challenges. For example, adding macros to the report would require the user to know how to write or run the macros, which are a type of code or script that automates certain tasks or actions on the report, such as filtering or calculating the data. Adding macros to the report could also expose the user to some security or compatibility issues, such as viruses, malware, or errors.

NEW QUESTION # 114
......

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