Practice Data Engineering (1.2.1) - Introduction to Advanced Data Science

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9 questions

Flashcard drill
3 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What does ETL stand for?
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Think about the stages of preparing data.
Question 2.
Why is data cleaning necessary?
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Consider the consequences of using dirty data.
3Question 3.
What does ETL mean?
- Extract, Transform, Load
- Encode, Transfer, Load
- Extract, Transfer, Load
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Consider each word's role in data management.
4Question 4.
True or False: Data cleaning is only necessary if you are dealing with a small dataset.
- True
- False
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Think about the impact of errors in any sized dataset.
Question 5.
Design a data cleaning approach for an online retailer's customer database with missing contact information and duplicate records.
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Think about what reliable data should look like.
Question 6.
Create a sample ETL flow for a hospital that needs to process patient data in real time for monitoring health trends. Explain each step.
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Consider the end goal of real-time health monitoring and what data is needed.

5 more questions in this section. Enroll free to practise them all.