NPTEL Business Intelligence & Analytics Week 2 Assignment Answers 2025
1. Data warehouses provide __________ tools for interactive analysis of multidimensional data of varied granularities.
- Data mining
- Online Analytical Processing (OLAP)
- Transaction processing
- Data visualization
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2. What was the primary business problem faced by AT&T Long Distance?
- Inefficient telemarketing campaigns
- Difficulty in acquiring new customers
- Lack of technology for data analysis
- Insufficient funding for marketing
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3. What is the purpose of data cleaning and integration techniques in the construction of a data warehouse?
- To enhance the speed of data retrieval.
- To ensure consistency in naming conventions, encoding structures, and attribute measures
- To permanently delete irrelevant data.
- To store data in multiple formats for redundancy.
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4. Which of the following best describes the “nonvolatile” nature of data in a data warehouse?
- Data is constantly changing and requires frequent updates
- Data remains stable and is not subject to regular deletions or modifications.
- Data is always accessed for real-time transactions.
- Data is stored temporarily and can be easily altered.
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5. An OLTP system usually adopts an _________ data model.
- Hierarchical
- Entity-Relationship
- Object-Relational
- Network
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6. What is the primary characteristic of OLAP system access patterns?
- Frequent updation and live alteration to the data
- Real-time transaction processing
- Primarily read-only operations
- Atomic transactions
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7. Why is it not recommended to process complex OLAP queries on operational databases?
- It can increase the risk of security breaches.
- It can lead to data inconsistencies.
- It can significantly degrade the performance of transactional operations.
- Incompatible with operational data structures.
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8. Which of the following is a key function of back-end tools and utilities in a data warehouse system?
- Query optimization
- Data extraction and transformation
- User interface design
- Data visualization
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9. What is a major challenge associated with data loading in large-scale data warehouses?
- Ensuring data consistency across multiple sources
- Managing distributed loading and performance optimization
- Preventing data loss during the loading process
- Ensuring data privacy and security during the loading process
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10. What is the primary difference between an enterprise data warehouse and a data mart?
- Enterprise data warehouses are more complex to implement and need more technical expertise than data marts
- Data marts are primarily used for strategic decision-making, while enterprise data warehouses are for tactical decisions.
- Enterprise data warehouses provide a comprehensive view of the entire organization’s data, while data marts focus on specific business areas.
- Data marts are more expensive to maintain than enterprise data warehouses.
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11. What is a potential drawback of using a virtual warehouse?
- Increased load on operational databases.
- High implementation costs.
- Limited scalability and performance.
- Difficulty in integrating data from multiple sources
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12. Consider a large-scale healthcare organization with multiple hospitals and clinics. What are the primary benefits of implementing a centralized database management system (DBMS) to manage patient records, medical history, and billing information?
- Improved data consistency and accuracy across different healthcare facilities, reducing errors and inconsistencies in patient records
- Enhanced data security and privacy through robust access controls and encryption to protect sensitive patient information.
- Efficient data retrieval and analysis to support clinical decision-making, research, and regulatory compliance.
- All of the above.
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13. A person transferred ₹2000 to his friend via a UPI application to contribute to a weekend trip. Which ACID property ensures that the transaction is either fully completed or completely rolled back?
- Atomicity
- Consistency
- Isolation
- Durability
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14. What is the purpose of normalization in a snowflake schema?
- To improve query performance.
- To reduce data redundancy.
- To increase data security.
- To simplify data loading and transformation
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15. Which data warehouse schema is typically more efficient for querying due to its simplified structure and less number of joins?
- Star schema
- Snowflake schema
- Both A & B are equally efficient
- It depends on the specific query workload
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