Authentic CompTIA Certification Exam DA0-001 Questions Answers

This is because redundant data is a type of data that is unnecessary or irrelevant for the analysis or purpose, which can affect the efficiency and performance of the analysis or process. Redundant data can be caused by having multiple data fields that store the same or similar information, such as patient height in inches and patient height in centimeters in this case. Redundant data can be eliminated or reduced by using data cleansing techniques, such as removing or merging the redundant data fields. The other types of data are not examples of data that is unnecessary or irrelevant for the analysis or purpose. Here is what they mean in terms of data quality:

• Dependent data is a type of data that relies on or is influenced by another data field or value, such as a formula or a calculation that uses other data fields or values as inputs or outputs. Dependent data can be useful or important for the analysis or purpose, as it can provide additional information or insights based on the existing data.
• Duplicate data is a type of data that is repeated or copied in a data set, which can affect the quality and validity of the analysis or process. Duplicate data can be caused by having multiple records or rows that have the same or similar values for one or more data fields or columns, such as customer ID or order ID. Duplicate data can be eliminated or reduced by using data cleansing techniques, such as removing or filtering out the duplicate records or rows.
• Invalid data is a type of data that is incorrect or inaccurate in a data set, which can affect the validity and reliability of the analysis or process. Invalid data can be caused by having values that do not match the expected format, type, range, or rule for a data field or column, such as an email address that does not have an @ symbol or a date that does not follow the YYYY-MM-DD format. Invalid data can be eliminated or reduced by using data cleansing techniques, such as validating or correcting the invalid values.

The option that the data analyst should use to best communicate the information to the manager is a summary with statistics, conclusions, and recommendations from the data analyst. A summary is a concise and clear way of presenting the main findings and insights from the data analysis report. A summary should include relevant statistics that support the conclusions and recommendations from the data analyst. A summary should also highlight the most important KPIs and measure the return on marketing investment in relation to the objectives of the online marketing campaign. The other options are not as effective as using a summary to communicate the information to the manager, as they either provide too much or too little information or do not address the manager’s needs or expectations. A real-time monitor may provide too much information that can be overwhelming or distracting for the manager who wants to see only the most important KPIs and measure the return on marketing investment. A self-service dashboard may provide too little information that can be insufficient or unclear for the manager who wants to see some guidance and interpretation from the data analyst. A spreadsheet of raw data may provide irrelevant or inaccurate information that can be confusing or misleading for the manager who wants to see some analysis and insights from the data analyst. Reference: [How to Write an Executive Summary for Your Data Analysis Report - Towards Data Science]

Explanation

Correct answer B. When data is at rest or in transit.

To provide maximum protection, encrypt data both in transit and at rest.