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 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?
Question
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 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?
Solution
In this situation, I would take the following steps:
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Communicate the Risks: The first step would be to clearly communicate the risks associated with using unclean data to the primary stakeholder. This includes potential inaccuracies in the results, misinterpretation of data, and the possibility of making incorrect decisions based on this data.
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Prioritize Data Cleaning: Despite the tight timeline, I would try to allocate some time to clean the most critical parts of the data. This could involve removing duplicates, handling null values, and correcting obvious errors. This would at least improve the quality of the data to some extent.
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Use Robust Methods: I would choose analytical methods that are robust to the issues in the data. For example, some statistical methods can handle missing data without requiring imputation.
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Document Everything: I would document all the issues found in the data and how they were handled (or not handled). This would provide a record of the potential limitations of the analysis.
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Present Results with Caveats: When presenting the results, I would clearly state the limitations due to the unclean data. This would help stakeholders understand the level of confidence they should have in the results.
Remember, the goal is to provide the best possible results under the given circumstances, while being transparent about the limitations.
Similar Questions
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.
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.
Wait for more data to come in to determine if it will support stakeholder anecdotesAsk your stakeholders to share the data they used to support their anecdotesRe-examine the data to determine if a mistake was made during data analysisAsk the team that prepared the table to re-analyze the dataYou reviewed a data summary table and noticed that the results are different from what stakeholders have anecdotally reported. Which of the following actions would you most likely take?
What was the most challenging part of cleaning the data?Why is cleaning and transposing data important for data analysis?If you had to clean this data again, what would you do differently? Why?
A data team at a manufacturing company finishes a project about production rates, so they delete the related files. However, they are later tasked with another production project, which the deleted files could have informed. What should the data team have done with the original project files?1 pointArchive themKeep them on their local driveSave them on a USB devicePrint them out
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