Business Intelligence & Analytics Week 5 NPTEL Assignment Answers 2025

NPTEL Business Intelligence & Analytics Week 5 Assignment Answers 2024

1. What concept does the phrase “turning data tombs into ‘golden nuggets’ of knowledge” signify with respect to data mining?

a. The transformation of extensive data reserves into valuable insights and knowledge
b. The replacement of conventional data repositories with intuitive decision-making tools
c. The extraction of specific data sets for expert systems’ utilization
d. The integration of data archives with cutting-edge data mining technologies

✅ Answer: a
Explanation: This phrase symbolizes the process of extracting useful knowledge from vast amounts of stored data—essentially the main purpose of data mining.

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2. Which step involves the extraction of data patterns using intelligent methods?

a. Data cleaning
b. Data integration
c. Data selection
d. Data mining

✅ Answer: d
Explanation: Data mining is the step where intelligent techniques are used to identify patterns and relationships in large data sets.

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3. What is the primary purpose of data mining in the context of the data age?

a. Storing and organizing massive amounts of data
b. Creating social networks and communities
c. Uncovering valuable information from vast data and converting it into organized knowledge
d. Supporting scientific experiments and observations

✅ Answer: c
Explanation: Data mining focuses on discovering hidden patterns or knowledge from massive datasets, aiding decision-making.

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4. Which technology contributed substantially to the evolution and wide acceptance of relational technology for efficient storage, retrieval, and management of large amounts of data?

a. Advanced indexing and accessing methods
b. Online transaction processing (OLTP)
c. Hierarchical database systems
d. Object-oriented database models

✅ Answer: a
Explanation: Efficient indexing and access methods improved performance and scalability of relational databases, making them widely adopted.

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5. What does the architecture of a data warehouse primarily aim to facilitate?

a. Data cleaning and integration
b. Advanced query optimization
c. Management decision making
d. Real-time data processing

✅ Answer: c
Explanation: A data warehouse is designed to support decision support systems by providing integrated, historical data.

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6. What is the primary advantage of using data warehouse systems for OLAP?

a. Providing detailed transactional views to users
b. Performing daily transaction analysis
c. Presenting data at different levels of abstraction
d. Enabling real-time data updates and modifications

✅ Answer: c
Explanation: OLAP (Online Analytical Processing) in data warehouses allows analysis of data from different perspectives (e.g., by time, region).

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7. What defines outliers in a dataset?

a. Objects that conform to the general behaviour or model of the data.
b. Data objects that are commonly discarded as exceptions.
c. Data that adhere strictly to statistical or distance measures.
d. Objects that deviate from the general behaviour or model of the data.

✅ Answer: d
Explanation: Outliers are unusual data points that don’t fit the expected pattern or distribution of a dataset.

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8. How does data mining benefit from scalable database technologies?

a. It diminishes efficiency and scalability on large datasets
b. It relies solely on traditional database systems
c. It enables high efficiency and scalability on large datasets
d. It limits scalability to small datasets for efficiency

✅ Answer: c
Explanation: Scalable databases allow efficient mining of large datasets, critical for big data analytics.

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9. What distinguishes Descriptive Analytics from other types of analytics?

a. It focuses on predicting future outcomes.
b. It identifies patterns and trends from past data.
c. It prescribes actions based on analyzed data.
d. It evaluates data in real-time for immediate decisions.

✅ Answer: b
Explanation: Descriptive analytics tells what has happened using historical data patterns and trends.

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10. Which phase in the knowledge discovery process involves the removal of noise and inconsistent data?

a. Data integration
b. Data transformation
c. Data cleaning
d. Data selection

✅ Answer: c
Explanation: Data cleaning prepares raw data by removing errors, inconsistencies, and noise before mining.

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11. In the context of data preprocessing, what is the purpose of data transformation?

a. To retrieve relevant data from the database
b. To remove noise and inconsistent data
c. To prepare data for mining by performing summary or aggregation operations
d. To evaluate interesting patterns based on specific measures

✅ Answer: c
Explanation: Data transformation reshapes data through operations like aggregation, normalization, and encoding for better mining outcomes.

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12. What is the fundamental characteristic of a relational database?

a. It consists of a collection of tables with unique names.
b. It uses graphs or networked structures to store data.
c. It primarily stores multimedia data and text data.
d. It represents the database as a set of entities and their relationships.

✅ Answer: a
Explanation: A relational database stores data in tables (relations) with rows and columns, each uniquely named.

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13. Which of the following can be called a major driver of Data Mining?

a. Decline of open-source technologies
b. Declining growth in manufacturing sector globally
c. Penetration of MOOC platforms
d. Rise of transaction processing systems/ERPs

✅ Answer: d
Explanation: ERP and transaction systems generate massive data, creating the need and opportunity for data mining.

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14. What does the “long tail” phenomenon refer to in business?

a. A marketing strategy focused on a narrow customer base
b. The distribution of sales that extends to less common products returning substantial profits
c. A strategy to increase product diversity without considering market demand
d. A method to minimize inventory costs in retail businesses

✅ Answer: b
Explanation: The long tail refers to niche products generating significant collective revenue, enabled by digital platforms.

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15. What can you infer from the following graph?

a. Less travelled destinations are growing more popular with each passing year
b. Top travel destinations are becoming more popular with each passing year
c. The growth of ICT evidently played an important role in making least popular places more popular
d. The growth of social media evidently played an important role in making least popular places more popular

✅ Answer: d
Explanation: Social media platforms often expose people to uncommon travel spots, boosting their popularity through user-shared content.