Given the following data table:
Which of the following are appropriate reasons to undertake data cleansing? (Select two).
Correct Answer:
BD
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.
The number of phone calls that the call center receives in a day is an example of:
Correct Answer:
D
Discrete data is a type of data that can only take certain values, usually whole numbers or integers. Discrete data can be counted, but not measured. For example, the number of students in a class, the number of books in a library, or the number of phone calls that a call center receives in a day are all examples of discrete data. Discrete data is different from continuous data, which can take any value within a range, and can be measured with precision. For example, the height of a person, the weight of a fruit, or the temperature of a room are all examples of continuous data. Therefore, the correct answer is D. References: [Discrete vs Continuous Data: Definition and Examples - Statistics How To], [Discrete Data - Definition and Examples | Math Goodies]
An analyst is currently working on a ticket for revamping a company-wide dashboard that has been in use for five years. Which of the following should be the first step in the development process?
Correct Answer:
A
The first step in the development process of revamping a company-wide dashboard should be to talk to the group that made the request to determine the desired goal. This would help to understand the needs, expectations, and preferences of the stakeholders, as well as the scope, purpose, and objectives of the project. Talking to the group that made the request would also help to establish a clear communication channel, build rapport and trust, and solicit feedback and suggestions.
Which of the following roles is responsible for ensuring an organization's data quality, security, privacy, and regulatory compliance?
Correct Answer:
B
Correct answer B. Data steward.
A data steward is responsible for leading an organization's data governance activities, which include data quality, security, privacy, and regulatory compliance.
A data analyst is asked to create a sales report for the second-quarter 2020 board meeting, which will include a review of the business??s performance through the second quarter. The board meeting will be held on July 15, 2020, after the numbers are finalized. Which of the following report types should the data analyst create?
Correct Answer:
A
A dynamic report is a type of report that shows data that changes or updates automatically based on certain criteria or parameters. A dynamic report can allow users to interact with the data, filter it, drill down into it, or visualize it in different ways. A dynamic report is suitable for situations where the data changes frequently or where real-time or near-real-time data is needed for decision making or analysis. In this case, the data analyst is asked to create a sales report for the second-quarter 2020 board meeting, which will include a review of the business??s performance through the second quarter. The board meeting will be held on July 15, 2020, after the numbers are finalized. This means that the data analyst does not need to show real-time or dynamic data, but rather a fixed and accurate view of the sales data for the second quarter. Therefore, a static report would be the best way to meet this stakeholder requirement. Therefore, the correct answer is A. References: [What are Dynamic Reports? | Sisense], Static vs Dynamic Reports - What??s The Difference? | datapine
