Chapter 5 Challenges in the Data Analytics Process

Which challenge arises when data is stored in isolated departments without integration?

• Data visualization

• Data silos

• Algorithm overfitting

• Ethical bias

What is a major pitfall of using incomplete datasets?

• Faster processing speeds

• Reduced storage costs

• Improved data privacy

• Inaccurate or biased conclusions

Which term describes the difficulty of managing extremely large datasets?

• Data redundancy

• Data overload

• Data governance

• Data anonymization

What is an example of confirmation bias in data analytics?

• Analyzing data for pre-existing belief

• Cleaning data for missing values

• Encrypting sensitive data

• Using random sampling methods

Which ethical issue involves using data without explicit user permission?Informed consent violation

• Algorithm optimization

• Data visualization

• Data integration

• Informed consent violation

Why is anonymization critical in ethical data practices?

• To reduce dataset size

• To simplify data analysis

• To improve computational speed

• To protect individual privacy

What ethical risk arises from using biased training data in machine learning?

• Enhanced model accuracy

• Reduced storage requirements

• Discrimination in algorithmic decisions

• Faster data processing

How can organizations address poor data quality?

• Avoid data validation

• Use smaller datasets

• Implement data cleaning

• Ignore missing values

What strategy helps break down data silos in large organizations?

• Reducing data collection

• Encouraging inter-department collaboration

• Using separate databases for each team

• Prioritizing manual data entry

Which practice reduces algorithmic bias in data analytics?Regularly auditing datasets

• Limiting stakeholder input

• Avoiding diverse data sources

• Regularly auditing datasets

• Using only historical data