University of California, Berkeley Data Management Class Set 6
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School
University of California, Berkeley *
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Course
140
Subject
Information Systems
Date
Apr 3, 2024
Type
Pages
3
Uploaded by UltraSnowBear26
University of California, Berkeley
Set 6
1. Machine Learning and Data Management
Short Answer:
●
How can machine learning algorithms improve data management practices?
Essay:
●
Discuss the integration of machine learning models within database systems for
predictive analytics. Include examples of use cases where this integration
provides significant advantages over traditional data analysis methods.
2. Cloud Data Storage Solutions
Practical:
●
Compare and contrast the use of object storage vs. block storage in cloud
environments. In what scenarios might one be preferred over the other?
Multiple Choice:
Which of the following is NOT a benefit of cloud-based data storage solutions?
A) Scalability
B) On-demand access
C) Reduced cost
●
D) Complete data privacy
3. Data Quality Management
Short Answer:
●
What is data profiling, and why is it important in the context of data quality
management?
Essay:
●
Explain the challenges in maintaining high data quality in big data environments.
Discuss strategies for data cleansing and validation to ensure the reliability and
accuracy of data analysis.
4. Ethical Use of Artificial Intelligence in Data Analysis
Multiple Choice:
Which of the following principles is considered fundamental for the ethical use of AI in
data analysis?
A) Transparency
B) Fairness
C) Accountability
●
D) All of the above
Practical:
●
Propose a framework for evaluating the ethical implications of an AI-driven data
analysis project. Include considerations for data sourcing, bias mitigation, and
impact assessment.
5. Real-Time Data Processing
Short Answer:
●
Describe the concept of stream processing and its importance in real-time data
analysis.
Essay:
●
Discuss the architectural differences between batch processing and stream
processing of data. Provide examples of use cases that are better suited for each
approach and explain why.
These questions are intended to provoke deep thought and comprehensive
understanding in students, covering the full spectrum from theoretical aspects to
practical applications of advanced data management concepts. They address the latest
trends and technologies in the field, preparing students for the challenges they may face
in their careers.
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