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CompTIA DA0-001 exam, also known as the CompTIA Data+ certification exam, is a certification exam designed to test an individual's knowledge and skills in the field of data management. DA0-001 exam is ideal for individuals who are looking to advance their careers in data management and administration. DA0-001 Exam covers a range of topics such as database management, data warehousing, data security, data analysis, and more. It is a vendor-neutral exam, which means that it is not tied to a specific technology or solution, making it a valuable certification for professionals working in any industry.
Free PDF Quiz CompTIA - Newest Exam DA0-001 Assessment
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CompTIA DA0-001 Exam covers a variety of topics related to data, including data management, data analysis, data visualization, and data security. Professionals who pass DA0-001 exam will be able to demonstrate their knowledge of these topics and their ability to work with data in a professional setting. CompTIA Data+ Certification Exam certification is relevant for professionals in a variety of fields, including business, healthcare, finance, and government.
CompTIA Data+ Certification Exam Sample Questions (Q151-Q156):
NEW QUESTION # 151
A development company is constructing a new Init 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 Init?
- A. $705,200
- B. $702,500
- C. $640,900
- D. $690,000
Answer: B
Explanation:
The correct answer is D. $702,500.
To find the price of the Rose unit, we need to use the average cost per square foot of the original floor plans.
The average cost per square foot is calculated by dividing the price by the square footage of each unit type.
Using the data from the table, we can do the following:
* Jasmine: $345,000 / 1,000 = $345 per square foot
* Orchid: $525,000 / 2,000 = $262.5 per square foot
* Azalea: $375,000 / 1,500 = $250 per square foot
* Tulip: $450,000 / 1,800 = $250 per square foot
The average cost per square foot of the original floor plans is the mean of these four values, which is ($345 +
$262.5 + $250 + $250) / 4 = $276.875 per square foot.
To find the price of the Rose unit, we need to multiply the average cost per square foot by the square footage of the Rose unit. The Rose unit has a square footage of 2,535, according to the table. Therefore, the price of the Rose unit is $276.875 x 2,535 = $702,421.875.
Rounding to the nearest whole number, we get$702,500as the price of the Rose unit.
NEW QUESTION # 152
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. $702,500
- C. $640,900
- D. $690,000
Answer: A
Explanation:
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 # 153
Each month an analyst needs to execute a data pull for the two prior months. Which of the following is the most efficient function for the analyst to use?
- A. System
- B. Date
- C. Logical
- D. Aggregate
Answer: B
Explanation:
The most efficient function for an analyst to execute a data pull for the two prior months would be the Date function. This function allows for the manipulation and formatting of date values within a database. Using Date functions, an analyst can dynamically calculate the start and end dates for the previous two months, ensuring that the data pull is accurate and automated without manual intervention.
For example, SQL functions like DATEADD and DATEDIFF can be used to determine the exact range of dates needed for the data pull. These functions can calculate the first and last day of the previous months relative to the current date, which is essential for monthly reporting and analysis.
Reference:
Discussions on Stack Overflow suggest using SQL date functions like DATEADD and DATEDIFF to dynamically extract data for previous months, which supports the use of Date functions12.
The use of Date functions is also recommended for ensuring that the data pull is not only efficient but also accurate, as it avoids potential errors associated with manual date entry3.
NEW QUESTION # 154
A data analyst has been asked to derive a new variable labeled "Promotion_flag" based on the total quantity sold by each salesperson. Given the table below:
Which of the following functions would the analyst consider appropriate to flag "Yes" for every salesperson who has a number above 1,000,000 in the Quantity_sold column?
- A. Date
- B. Logical
- C. Aggregate
- D. Mathematical
Answer: C
NEW QUESTION # 155
Which of the following is a best practice when updating a legacy data source?
- A. Removing the data source from production
- B. Placing old data in new fields
- C. Keeping only the most recent data
- D. Creating a codebook to document field changes
Answer: D
Explanation:
When updating a legacy data source, it is a best practice to create a codebook to document field changes. A codebook serves as a detailed guide and record of the data structure, definitions, and any transformations or modifications made to the data fields. This documentation is crucial for maintaining data integrity, ensuring consistency, and facilitating future data use and understanding. It provides a reference that can be invaluable for data analysts, developers, and any stakeholders who need to work with the data.
Creating a codebook is preferred over placing old data in new fields, which can lead to confusion and data integrity issues. Keeping only the most recent data may result in the loss of valuable historical information. Removing the data source from production is not a practice related to updating data but rather to retiring a data source1234.
References:
* Legacy Data Migration: A Comprehensive Guide | OpenGeeksLab
* How to Successfully Complete Legacy Database Migration
* Methods for Saving and Integrating Legacy Data - DATAVERSITY
* Legacy Data Digitization - Learn The Best Practices
NEW QUESTION # 156
......
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