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CompTIA DA0-001 exam is an important certification for IT professionals who are involved in data management. CompTIA Data+ Certification Exam certification is recognized worldwide as a mark of excellence in data management, and the certification program provides a comprehensive curriculum that covers a range of topics related to data management. DA0-001 exam is designed to test the candidate's knowledge of data management concepts and techniques, and passing the exam is a significant achievement for any IT professional looking to establish themselves as an expert in data management.

CompTIA DA0-001 Exam, also known as the CompTIA Data+ Certification, is a highly respected certification exam in the IT industry. DA0-001 exam is designed to test a candidate's understanding of the fundamentals of data management, including data collection, analysis, storage, and dissemination. CompTIA Data+ Certification Exam certification is ideal for those who work in data-driven industries, such as healthcare, finance, and government.

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CompTIA Data+ Certification Exam Sample Questions (Q237-Q242):

NEW QUESTION # 237
Which action is mandated by the Gramm-Leach-Bliley Act (GLBA) Safeguards Rule?

Answer: B


NEW QUESTION # 238
A data analyst has been asked to organize the table below in the following ways:
By sales from high to low -
By state in alphabetic order -

Which of the following functions will allow the data analyst to organize the table in this manner?

Answer: D

Explanation:
Sorting is the function that will allow the data analyst to organize the table in the desired manner. Sorting means arranging the data in a specific order, such as ascending or descending, based on one or more criteria.
Sorting can be applied to any column in the table, such as sales or state. References: CompTIA Data+ Certification Exam Objectives, page 11


NEW QUESTION # 239
A data set for sales per month includes the following data:

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

Answer: D


NEW QUESTION # 240
An analysts building a monthly report for production and wants to ensure the audience is aware of its once-a-month cadence. Which of the following is the MOST important to convey that information?

Answer: B

Explanation:
Explanation
This is because the date of the dashboard build is the most important component to convey that information, which is the once-a-month cadence of the monthly report for production. The date of the dashboard build can convey that information by indicating when the dashboard was created or updated, as well as showing the frequency or interval of the dashboard creation or update. For example, the date of the dashboard build can convey that information by displaying a date format that includes the month and year, such as January 2020, February 2020, etc., or by displaying a text format that includes the word "monthly", such as Monthly Report for Production - January 2020, Monthly Report for Production - February 2020, etc. The other components are not the most important components to convey that information. Here is why:
The data refresh date is a component that indicates when the data on the dashboard was refreshed or retrieved from the source or system, such as a database, a cloud service, or a web application. The data refresh date does not convey that information, but rather conveys how current or up-to-date the data on the dashboard is.
A report summary is a component that provides an overview or a highlight of the main findings or insights from the dashboard, such as key metrics, indicators, or trends. A report summary does not convey that information, but rather conveys what the dashboard is about or what it shows.
Frequently asked questions is a component that provides answers or explanations to common or expected questions from the audience or users of the dashboard, such as how to use or interpret the dashboard, what are the assumptions or limitations of the dashboard, etc. Frequently asked questions does not convey that information, but rather conveys how to understand or interact with the dashboard.


NEW QUESTION # 241
Which of the following would a data analyst look for first if 100% participation is needed on survey results?

Answer: B

Explanation:
Explanation
Missing data is a type of data quality issue that occurs when some values in a data set are not recorded or available. Missing data can affect the validity and reliability of survey results, especially if the missing values are not random or ignorable. Missing data can also reduce the sample size and the statistical power of the analysis12 If 100% participation is needed on survey results, a data analyst would look for missing data first, because missing data would indicate that some participants did not complete or submit the survey, or that some responses were not recorded or transmitted correctly. A data analyst would need to identify the causes and patterns of missing data, and apply appropriate methods to handle or prevent missing data, such as imputation, deletion, weighting, or follow-up12


NEW QUESTION # 242
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