DA0-001 QUESTIONS AND ANSWERS: COMPTIA DATA+ CERTIFICATION EXAM & DA0-001 PRACTICE TEST

DA0-001 Questions and Answers: CompTIA Data+ Certification Exam & DA0-001 Practice Test

DA0-001 Questions and Answers: CompTIA Data+ Certification Exam & DA0-001 Practice Test

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CompTIA Data+ certification exam covers a wide range of topics related to data management, including data collection, processing, analysis, visualization, and interpretation. It also covers data governance, security, and privacy issues, as well as data storage technologies and tools. DA0-001 Exam is designed to test candidates' ability to work with different types of data, such as structured, unstructured, and semi-structured data, using a variety of tools and techniques.

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CompTIA DA0-001 Certification Exam is designed for IT professionals who are responsible for managing data in their organizations. CompTIA Data+ Certification Exam certification is particularly beneficial for professionals who work in roles such as data analysts, data administrators, data architects, and database developers. Having this certification can help individuals advance in their careers by demonstrating their expertise and knowledge in the field of data management.

CompTIA DA0-001 exam is an excellent choice for professionals who want to enhance their career prospects in the data management field. CompTIA Data+ Certification Exam certification validates the candidate's ability to manage and secure data, analyze data, and understand data storage technologies. CompTIA Data+ Certification Exam certification is internationally recognized and can lead to better job opportunities and higher salaries. Candidates can register for the exam through the Pearson VUE website, and the exam fees vary by location.

CompTIA Data+ Certification Exam Sample Questions (Q231-Q236):

NEW QUESTION # 231
Given the following data table:

Which of the following are appropriate reasons to undertake data cleansing? (Select two).

  • A. Normalized data
  • B. Non-parametric data
  • C. Missing data
  • D. Duplicate data
  • E. Redundant data
  • F. Invalid data

Answer: C,F

Explanation:
Data cleansing is a critical process in data analytics to ensure the accuracy and quality of data. The reasons to undertake data cleansing include:
* Missing Data (B): Missing data can lead to incomplete analysis and biased results. It is essential to identify and address gaps in the dataset to maintain the integrity of the analysis1.
* Invalid Data (D): Invalid data includes entries that are out of range, improperly formatted, or illogical (e.
g., a negative age). Such data can corrupt analysis and lead to incorrect conclusions1.
Other options, such as non-parametric data (A), are not inherently errors but refer to a type of data that doesn' t assume a normal distribution. Duplicate data and redundant data (E) could also be reasons for data cleansing, but they are not listed as options to select from in the provided image details. Normalized data (F) refers to data that has been processed to fit into a certain range or format and is typically not a reason for data cleansing.
References:
* Understanding the importance of data quality and the impacts of missing and invalid data on research outcomes1.
* Best practices in data cleansing2.
Data cleansing is required for various reasons, two of which are missing data (B) and invalid data (D). From the table provided, we can infer the necessity of cleansing in the context of ensuring data integrity and consistency. Missing data refers to the absence of data where it is expected, which can hinder analysis due to incomplete information. Invalid data refers to data that is incorrect, out of range, or in an inappropriate format, which can lead to inaccuracies in any analysis or report. Both these issues can significantly affect the outcomes of any data-related operations and thus need to be rectified through the data cleansing process.


NEW QUESTION # 232
An analyst has received the requirements for an internal user dashboard. The analyst confirms the data sources and then creates a wireframe. Which of the following is the NEXT step the analyst should take in the dashboard creation process?

  • A. Create subscriptions.
  • B. Get stakeholder approval.
  • C. Optimize the dashboard.
  • D. Deploy to production.

Answer: B

Explanation:
Getting stakeholder approval is the next step the analyst should take in the dashboard creation process, after confirming the data sources and creating a wireframe. Stakeholder approval means getting feedback and validation from the intended users or clients of the dashboard, to ensure that it meets their expectations and requirements. This step helps to avoid rework and ensure customer satisfaction. References: CompTIA Data+ Certification Exam Objectives, page 14


NEW QUESTION # 233
Given the diagram below:

Which of the following steps is missing?

  • A. Validate the data types.
  • B. Normalize the data.
  • C. Remove redundant data.
  • D. Connect to the data API.

Answer: C

Explanation:
The missing step in the Extract, Transform, Load (ETL) process is typically the cleaning step, which involves removing redundant data or deduplication. This step is crucial in the ETL process to ensure that the data loaded into the destination is accurate and not inflated by duplicate records. The other options, like validating data types and connecting to the data API, are important but do not fit into the standard ETL process steps as a cleaning operation. Normalizing the data is part of the 'Transform' step, which was already listed.


NEW QUESTION # 234
A data analyst is asked on the morning of April 9, 2020, to create a sales report that identifies sales year to date. The daily sales data is current through the end of the day. Which of the following date ranges should be on the report?

  • A. January 1, 2020 to April 9, 2020
  • B. January 1, 2020 to April 8, 2020
  • C. January 1, 2020 to April 1, 2020
  • D. January 1, 2020 to April 7, 2020

Answer: A


NEW QUESTION # 235
What technique is used to swap the values in rows and columns of tabular data?

  • A. Regression.
  • B. Classification.
  • C. Association.
  • D. Transposition.

Answer: D


NEW QUESTION # 236
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