RELIABLE COMPTIA DA0-001 SOURCE - DA0-001 TEST QUESTIONS PDF

Reliable CompTIA DA0-001 Source - DA0-001 Test Questions Pdf

Reliable CompTIA DA0-001 Source - DA0-001 Test Questions Pdf

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CompTIA Data+ Certification is a valuable credential for IT professionals who want to demonstrate their expertise in data management. CompTIA Data+ Certification Exam certification validates the candidate's ability to work with different types of data, understand data storage and organization, and apply data analysis and security techniques. It is recognized by employers and organizations worldwide and can help individuals to advance their careers in IT.

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CompTIA DA0-001 Exam is a vendor-neutral certification, which means that it is not tied to any specific software or hardware platform. This makes it an ideal certification for professionals who work in a variety of industries and use different tools and technologies to manage and analyze data.

CompTIA Data+ Certification Exam Sample Questions (Q53-Q58):

NEW QUESTION # 53
While reviewing survey data, an analyst notices respondents entered "Jan," "January," and "01" as responses for the month of January. Which of the following steps should be taken to ensure data consistency?

  • A. Delete any of the responses that do not have "January" written out.
  • B. Replace any of the responses that have "01".
  • C. Sort any of the responses that say "Jan" and update them to "01".
  • D. Filter on any of the responses that do not say "January" and update them to "January".

Answer: D


NEW QUESTION # 54
An analyst is updating a customer contacts database with information obtained from a survey of new customers. Which of the following data manipulation techniques should the analyst use?

  • A. Append
  • B. Transform
  • C. Join
  • D. Blend

Answer: A

Explanation:
Comprehensive and Detailed In-Depth
When incorporating new customer information from a survey into an existing customer contacts database, the appropriate data manipulation technique is:
Option B:Append
Rationale:Appending involves adding new records to the end of an existing dataset without altering the existing data. In this scenario, the analyst adds the new customer information as additional records in the database.
Option A:Join
Rationale:Joining combines data from two or more tables based on a related column, creating a new dataset with combined information. This is not necessary when simply adding new records.
Option C:Transform
Rationale:Transformation involves changing the format, structure, or values of data. While important in data processing, it doesn't pertain to adding new records.
Option D:Blend
Rationale:Data blending combines data from different sources into a single dataset, often used in analysis rather than updating a database with new records.
Reference:
partners.comptia.org


NEW QUESTION # 55
A data analyst has been asked to create a sales report that calculates the rolling 12-month average for sales. If the report will be published on November 1, 2020, which of the following months shouts the report cover?

  • A. November 1, 2019 to October 31, 2020
  • B. October 31, 2019 to October 31, 2020
  • C. October 1, 2019 to October 31, 2020
  • D. October 31, 2020 to November 1, 2021

Answer: A


NEW QUESTION # 56
Which of the following data cleansing issues will be fixed when a DISTINCT function is applied?

  • A. Missing data
  • B. Invalid data
  • C. Redundant data
  • D. Duplicate data

Answer: D

Explanation:
This is because duplicate data refers to data that is repeated or copied in a data set, which can affect the quality and validity of the analysis. A DISTINCT function is a type of function that removes duplicate values from a column or a table, leaving only unique values. For example, a DISTINCT function in SQL that can achieve this is:

The other data cleansing issues will not be fixed by applying a DISTINCT function. Here is why:
Missing data refers to data that is absent or incomplete in a data set, which can affect the accuracy and reliability of the analysis. A DISTINCT function does not help with missing data, because it does not fill in or impute the missing values.
Redundant data refers to data that is unnecessary or irrelevant for the analysis, which can affect the efficiency and performance of the analysis. A DISTINCT function does not help with redundant data, because it does not remove or filter out the redundant values.
Invalid data refers to data that is incorrect or inaccurate in a data set, which can affect the validity and reliability of the analysis. A DISTINCT function does not help with invalid data, because it does not validate or correct the invalid values.


NEW QUESTION # 57
Consider this dataset showing the retirement age of 11 people, in whole years:
54, 54, 54, 55, 56, 57, 57, 58, 58, 60, 60
This tables show a simple frequency distribution of the retirement age data.

  • A. 0
  • B. 1
  • C. 2
  • D. 3

Answer: B

Explanation:
A measure of central tendency (also referred to as measures of centre or central location) is a summary measure that attempts to describe a whole set of data with a single value that represents the middle or centre of its distribution.
There are three main measures of central tendency: the mode, the median and the mean. Each of these measures describes a different indication of the typical or central value in the distribution.
What is the mode?
The mode is the most commonly occurring value in a distribution.
The most commonly occurring value is 54, therefore the mode of this distribution is 54 years.


NEW QUESTION # 58
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