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To prepare for the CompTIA DA0-001 exam, candidates can take advantage of various study resources, such as online courses, study guides, and practice exams. It is important to have a solid understanding of data management concepts and principles, as well as practical experience working with data, before attempting the exam. With proper preparation and study, candidates can increase their chances of passing the exam and achieving the CompTIA Data+ Certification.

CompTIA DA0-001 (CompTIA Data+ Certification) Certification Exam is a globally recognized certification designed to validate an individual's knowledge and skills in managing and analyzing data. CompTIA Data+ Certification Exam certification is ideal for IT professionals who are responsible for collecting, analyzing, and interpreting data to support business decisions. CompTIA Data+ Certification Exam certification exam covers a wide range of topics, including data management, data analysis, data visualization, and data security.

CompTIA DA0-001 is the certification exam for the CompTIA Data+ certification. CompTIA Data+ Certification Exam certification is designed to validate the skills and knowledge of candidates who work with data, whether it's managing and analyzing data or working with database technologies. DA0-001 exam is designed to test the candidate's understanding of data management, data analysis, and database technologies.

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CompTIA Data+ Certification Exam Sample Questions (Q24-Q29):

NEW QUESTION # 24
A development company is constructing a new unit in its apartment complex. The complex has the following floor plans:

Using the average cost per square foot of the original floor plans, which of the following should be the price of the Rose unit?

A. $705,200
B. $640,900
C. $690,000
D. $702,500

Answer: A

Explanation:
This is because the price of the Rose unit can be estimated using the average cost per square foot of the original floor plans, which are Jasmine, Orchid, Azalea, and Tulip. To find the average cost per square foot of the original floor plans, we can use the following formula:

Plugging in the values from the original floor plans, we get:

To find the price of the Rose unit, we can use the following formula:

Plugging in the values from the Rose unit, we get:

Therefore, the price of the Rose unit should be $705,200, using the average cost per square foot of the original floor plans.

NEW QUESTION # 25
Which of the following technologies would be best suited for creating a multiple linear regression model?

A. SQL
B. Tableau
C. Microsoft Power Bl
D. R

Answer: D

Explanation:
R is a statistical programming language that is specifically designed for data analysis and statistical modeling, making it highly suitable for creating a multiple linear regression model. It has extensive libraries such as lm() for linear modeling, which simplifies the process of model creation, diagnostics, and interpretation. R also provides robust tools for data manipulation and visualization, which are essential for preparing data for regression analysis and understanding the results123.
While Microsoft Power BI, SQL, and Tableau have capabilities for regression analysis, they are more limited compared to R. Power BI and Tableau are primarily business intelligence tools that offer some built-in analytics capabilities, but they are not as comprehensive as R. SQL is a database query language that can perform some statistical calculations, but it is not inherently designed for statistical modeling4567.
Reference:
Multiple Linear Regression in R: Tutorial With Examples - DataCamp1.
Implementing linear regression in Power BI - SQLBI5.
Choosing a Predictive Model - Tableau6.
How Predictive Modeling Functions Work in Tableau7.

NEW QUESTION # 26
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. Parsing
B. Transposing
C. Imputing
D. Concatenating

Answer: A

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 # 27
An analyst needs to summarize the number of people in Chicago in 2022 using the following set of data:

Which of the following steps should the analyst use to provide results? (Select two).

A. Sorting
B. Aggregation
C. Indexing
D. Cleaning
E. Filtering
F. Replacing

Answer: B,E

NEW QUESTION # 28
Which of the following is a best practice when updating a legacy data source?

A. Placing old data in new fields
B. Creating a codebook to document field changes
C. Keeping only the most recent data
D. Removing the data source from production

Answer: B

NEW QUESTION # 29
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