1.2.1 - Data Engineering
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions
What does ETL stand for?
💡 Hint: Think about the stages of preparing data.
Why is data cleaning necessary?
💡 Hint: Consider the consequences of using dirty data.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does ETL mean?
💡 Hint: Consider each word's role in data management.
True or False: Data cleaning is only necessary if you are dealing with a small dataset.
💡 Hint: Think about the impact of errors in any sized dataset.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Design a data cleaning approach for an online retailer's customer database with missing contact information and duplicate records.
💡 Hint: Think about what reliable data should look like.
Create a sample ETL flow for a hospital that needs to process patient data in real time for monitoring health trends. Explain each step.
💡 Hint: Consider the end goal of real-time health monitoring and what data is needed.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.