
Data Engineering Myths and Facts
Quiz
•
Science
•
KG
•
Practice Problem
•
Hard
Po Chiu
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5 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is a myth about data engineering programs?
A) Data engineering is only about building data pipelines.
B) Data engineers only work with structured data.
C) Data engineering involves both software engineering and data science skills.
D) Data engineers require knowledge of databases and data storage technologies.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is true about the role of a data engineer?
A) Data engineers focus solely on machine learning model development.
B) Data engineers primarily work with historical data, not real-time data.
C) Data engineers ensure the data is accessible and usable for analysis.
D) Data engineers do not need to understand business contexts or requirements.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which statement is a myth about the skills needed in data engineering?
A) Understanding of data integration tools is crucial for data engineers.
B) Data engineers must be proficient in at least one programming language.
C) Data engineers do not need to understand cloud computing platforms.
D) Knowledge of data modeling and ETL processes is important for data engineers.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is true about data engineering programs?
A) They teach only the technical skills needed for data manipulation.
B) They equip students with skills in data management, processing, and optimization.
C) They are solely focused on teaching SQL and database management.
D) They avoid topics on data security and data governance.
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which statement is a myth regarding the outcomes of data engineering programs?
A) Graduates only qualify for roles in data pipeline development.
B) Graduates are well-prepared to handle large-scale data infrastructures.
C) Data engineering graduates only work behind the scenes and never interact with business units.
D) Graduates understand how to implement data flows that support decision making.
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