Practice Why Data Cleaning Matters (5.3) - Data Cleaning and Preprocessing

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8 questions

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6 questions · about 4 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is data cleaning?
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Think about tasks that ensure your data is correct.
Question 2.
Give one reason why accuracy is important.
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Consider the consequences of faulty conclusions.
3Question 3.
What is one key reason for data cleaning?
- To analyze raw data
- To improve data accuracy
- To visualize data
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Think about what bad data can do.
4Question 4.
True or False: Inconsistent data can result in contradictory insights.
- True
- False
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Consider the nature of contradictions in data!
Question 5.
You are given a dataset with mixed data types for a single column. Suggest a method for cleaning this data.
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Think about how you would ensure uniform entries.
Question 6.
Consider a scenario where a business was negatively impacted by relying on flawed data. Analyze the potential impact and suggest systematic approaches to enhance data integrity.
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Think of how prevention steps could have changed the outcome.

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