Now, the vice president presents a situation having to do with resolving challenges and meeting stakeholder expectations. Consider and respond to the following question.You’re working with a dataset that the data analytics coordinator should have cleaned, but it turns out that it wasn’t. Your supervisor thought the dataset was ready for use, but you discover nulls, redundant data, and other issues. The project is due in less than two weeks. How would you handle that situation?1 pointContact the data analytics coordinator and insist they clean the dataset immediately so you don’t miss your project deadline.Call a formal meeting with the data analytics team to solve the problem. Do not invite the associate data analyst, as they clearly don’t have time to help.Communicate with the data analytics coordinator about the issue and offer to work together to clean the data so the project doesn’t fall behind.Email your supervisor to let them know the associate data analyst did not complete their assigned task.

Question 8Scenario 2 continuedNow, the vice president presents a situation having to do with resolving challenges and meeting stakeholder expectations. Consider and respond to the following question.You’re working on a rush project, and you discover your dataset is not clean. Even though it has numerous nulls, redundant data, and other issues, the primary stakeholder insists that you move ahead and use it anyway. The project timeline is so tight that there simply isn’t enough time for cleaning. How would you handle that situation?1 pointCommunicate the situation to your supervisor and ask for advice on how to handle the situation with the stakeholder.Contact the stakeholder’s boss to let them know about the issue and ask for help managing the stakeholder’s expectations.The stakeholder is in charge. It's best to do as they say and use the unclean dataset.Clean the data as quickly as you can. It’s not perfect, but it’s better than it was before, and this way you can meet the deadline.

You’re working on a rush project, and you discover your dataset is not clean. Even though it has numerous nulls, redundant data, and other issues, the primary stakeholder insists that you move ahead and use it anyway. The project timeline is so tight that there simply isn’t enough time for cleaning. How would you handle that situation?1 pointThe stakeholder is in charge. It's best to do as they say and use the unclean dataset.Contact the stakeholder’s boss to let them know about the issue and ask for help managing the stakeholder’s expectations.Clean the data as quickly as you can. It’s not perfect, but it’s better than it was before, and this way you can meet the deadline.Communicate the situation to your supervisor and ask for advice on how to handle the situation with the stakeholder.

Question 4A data analyst feels overworked. They often stay late to finish work, and have started missing deadlines. Their supervisor emails them another project to complete, and this causes the analyst even more stress. How should they handle this situation?1 pointWait a few minutes to think it over, then respond with a meeting request to discuss this project and the general workloadWalk into the supervisor’s office and tell them to give the project to someone elseRespond immediately, letting the supervisor know their expectations are unreasonableAccept the new project right away and hope to not miss another deadline

Question 2As a data analyst, you will need to keep the big picture in mind throughout any project when verifying data cleaning. What must the analyst do to take a big picture view of the project? Select all that apply.1 pointConsider the business problemConsider the dataConsider the goalConsider the reporting

What are some benefits of documenting any errors you find while data cleaning? Select all that apply.1 pointSave time by not repeating errors in the futureKeep track of changesHaving a backup of your datasetMore efficient troubleshooting