Chapter 12: Big Data and Data Science Applications MCQs

Which of the following best describes big data?

• A small collection of structured data used for analytics

• Extremely large and complex datasets that require specialized tools for analysis

• Data that can only be analyzed using traditional relational databases

• A simple data processing system used for cloud storage

What is the primary challenge of big data?

• Data redundancy

• Processing large volumes, velocity, and variety of data efficiently

• Reducing internet bandwidth usage

• Eliminating the need for storage solutions

Which of the following is NOT considered one of the five V’s of big data?

• Velocity

• Veracity

• Virtualization

• Variety

How does predictive analytics use big data?

• By summarizing past trends without forecasting

• By using historical data to predict future trends and behaviors

• By storing data without performing any computations

• By minimizing the use of AI algorithms in data processing

Why is real-time data processing important in big data analytics?

• It increases storage requirements

• It enables businesses to make immediate and informed decisions

• It slows down data retrieval processes

• It removes the need for machine learning models

Which industry benefits the most from big data’s predictive analytics?

• Fashion

• Retail

• Healthcare

• Gardening

What is the role of data lakes in big data?

• They store structured and unstructured data in its raw form

• They delete redundant information from big data systems

• They reduce the security risks associated with data breaches

• They convert all unstructured data into structured databases

What differentiates a NoSQL database from a traditional relational database in big data processing?

• NoSQL databases are more structured than relational databases

• NoSQL databases can handle large-scale unstructured data more efficiently

• Relational databases process data faster than NoSQL databases

• NoSQL databases require a predefined schema before data insertion

Why is data governance essential in big data management?

• It ensures ethical and legal compliance in data handling

• It eliminates data storage requirements

• It prevents data duplication across multiple platforms

• It restricts access to cloud-based analytics

How does artificial intelligence enhance big data analytics?

• By replacing the need for data scientists

• By improving data classification, pattern detection, and automation

• By reducing the importance of data security

• By eliminating the need for machine learning models