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CompTIA Data+ Certification Exam Questions and Answers

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Viewing questions 81-90 out of questions

Questions # 81:

A data architect is designing a data solution for a retail clothing store chain. Each store has a database that tracks sales transactions. The data architect needs to create a summary table that will be used for a senior executive dashboard. The summary table should not contain duplicate store information. Which of the following should the data architect create?

Options:

A check constraint

A primary key

A foreign key

A unique constraint

Answer

Explanation

Aunique constraintensures that no duplicate values exist in a specified column of a table. This is essential for creating summary tables where each store should only appear once in the dataset.

[Reference:CompTIA Data+ DA0-001 Official Guide, , ]

Questions # 82:

Given the following:

Question # 82

Which of the following is the most important thing for an analyst to do when transforming the table for a trend analysis?

Options:

Fill in the missing cost where it is null.

Separate the table into two tables and create a primary key

Replace the extended cost field with a calculated field.

Correct the dates so they have the same format.

Answer

Explanation

Correcting the dates so they have the same format is the most important thing for an analyst to do when transforming the table for a trend analysis. Trend analysis is a method of analyzing data over time to identify patterns, changes, or relationships. To perform a trend analysis, the data needs to have a consistent and comparable format, especially for the date or time variables.

In the example, the date purchased column has two different formats: YYYY-MM-DD and MM/DD/YYYY. This could cause errors or confusion when sorting, filtering, or plotting the data over time. Therefore, the analyst should correct the dates so they have the same format, such as YYYY-MM-DD, which is a standard and unambiguous format.

Questions # 83:

A data set for sales per month includes the following data:

Question # 83

Which of the following cleaning and profiling methods should be applied to the data set?

Options:

Data outliers

Invalid data

Duplicate data

Data type validation

Answer

Questions # 84:

Consider two different datasets, one with gas prices and the other with food prices. Which of the following measures is most affected by outliers?

Options:

Absolute value

Mode

Median

Mean

Answer

Explanation

Themean(average) is the most sensitive measure when it comes to outliers. If a dataset contains extreme values (either very high or very low), theydisproportionately affect the mean, making it a less robust measure of central tendency.

[Reference:CompTIA Data+ DA0-001 Official Guide, , ]

Questions # 85:

A gambler thinks that a coin is fair and is equally likely to turn up heads or tails when the coin is flipped. Which of the following tests should the gambler use to fest this hypothesis?

Options:

t-test

Chi-squared test

Rank sum test

Ratio test

Answer

Questions # 86:

Given the image below:

Question # 86

Which of the following file formats is depicted?

Options:

JSON

CSV

XML

HTML

Answer

Explanation

The image depicts a snippet of code in the JSON format, which stands for JavaScript Object Notation. JSON is a lightweight data-interchange format that is easy for humans to read and write and easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language and is commonly used to transmit data in web applications.

CSV, or Comma-Separated Values, is a simple file format used to store tabular data, such as a spreadsheet or database. It uses commas to separate values.

XML, or eXtensible Markup Language, is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable.

HTML, or HyperText Markup Language, is the standard markup language for documents designed to be displayed in a web browser.

[References:, JSON.org - Introducing JSON1, W3Schools - JSON Introduction2, Mozilla Developer Network - JSON3, , , ]

Questions # 87:

During data profiling, an analyst decides to recode the status column in the following data set:

Question # 87

Which of the following data concerns explains why the analyst wants to take this action?

Options:

Redundancy

Duplication

Invalidity

Inconsistency

Answer

Explanation

The ‘Status’ column in the dataset shows different terms such as “yes”, “completed”, “done”, and “Y” that likely represent the same outcome - that a task has been completed. This variation in terms leads to inconsistency within the data. Data profiling aims to ensure that data is consistent, among other quality metrics, to facilitate accurate analysis and reporting. By recoding the ‘Status’ column, the analyst seeks to address this inconsistency, ensuring that all entries indicating completion are represented uniformly. This enhances the data quality and usability for subsequent data analysis tasks.References:

The action of recoding is taken to standardize the data entries and eliminate inconsistencies, which is crucial for maintaining data integrity and ensuring reliable data analysis.

Questions # 88:

An analyst for a concert venue is analyzing the number of tickets sold for a recent event. Which of the following types of data is the number of sold tickets an example of?

Options:

Ordinal

Continuous

Nominal

Discrete

Answer

Explanation

The number of tickets sold representsdiscrete data, as it consists of countable, distinct values (e.g., 1, 2, 3, etc.). Discrete data cannot take on fractional values within the count and is contrasted with continuous data, which can take on any value within a range.

CompTIA Data+ Reference:

CompTIA Data+ Study Guide (Exam DA0-001), Chapter 2: Data Types and Structures, Section “Types of Quantitative Data: Discrete vs. Continuous”, Official CompTIA CertMaster Learn for Data+, Module 2.2 “Understanding Discrete Data”.

Questions # 89:

An analyst collected data that includes primary account numbers, expiration dates, and service codes. Which of the following data governance classifications is used to describe this data?