Business Intelligence & Analytics Week 1 Nptel Answers
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Nptel Business Intelligence & Analytics Week 1 Answers (Jan-Apr 2026)
Que1. Which step is defined as the extraction of non-obvious patterns from large datasets using intelligent methods?
a) Knowledge Discovery
b) Data integration
c) Data selection
d) Data mining
Que2. According to the lecture, Google operates as a “two-sided market” facilitated by matchmaking algorithms. Which of the following pairs accurately identifies the two distinct groups that the platform connects to generate revenue?
a) Information Seekers and Content Publishers
b) Search Engine Users and Advertisers
c) Data Scientists and Algorithm Developers
d) Digital Service Subscribers and Cloud Storage Providers
Que3. Which of the following is an example of unstructured data in a hospital information system?
a) Doctor’s handwritten or typed clinical notes
b) Patient admission records stored in database tables
c) Laboratory test results recorded in numeric form
d) Standardized patient demographics forms
Que4. Which of the following best describes the core objective of data mining?
a) Efficiently storing and archiving massive datasets
b) Creating social networks and communities
c) Converting raw data into organized, useful knowledge
d) Supporting scientific experiments and observations
Que5. Automatically organizing books into predefined categories in a library system is an example of ________.
a) clustering
b) unsupervised learning
c) supervised learning
d) reinforcement learning
Que6. True or False: Analyzing past airline travel records to report that ‘trips to the top 30 tourist destinations dropped by 10%’ is an example of descriptive data mining.
a) True
b) False
Que7. ________ refers to data objects that deviate from the general behaviour or model of the dataset and can be especially important in applications such as fraud detection.
a) Clusters
b) Outliers
c) Attributes
d) Outbounds
Que8. Which statement correctly describes a key function of a data warehouse?
a) It merges data from multiple sources and structures it into multidimensional data cubes
b) It stores only real-time transactional updates for immediate processing
c) It replaces indexing methods by eliminating the need for optimized query processing
d) It restricts data to a single time period to ensure consistency
Que9. In business intelligence, clustering is mainly used:
a) To create data warehouses
b) To enhance data visualization
c) To store historical data in standardized formats
d) To group customers based on similar behaviours or attributes
Que10. A key structural feature of a relational database is that it is organized as ________.
a) a set of interconnected graphs
b) a collection of tables with unique names
c) a repository mainly for multimedia files
d) a network of entities linked through pointers
Que11. The long tail phenomenon describes how businesses earn revenue from:
a) The cumulative sales of many niche items that generate significant revenue
b) The cumulative sales of popular items that generate significant revenue
c) Minimizing inventory costs to maximize profit
d) Offering product diversity based on market demand
Que12. What is the correct sequence of steps in data preparation for Knowledge Discovery from Data (KDD)?
a) Data cleaning, data integration, data transformation, data selection
b) Data cleaning, data integration, data visualization, data selection
c) Data cleaning, data standardization, data transformation, data selection
d) Data cleaning, data standardization, data normalization, data selection
Que13. The architecture of a data warehouse is primarily designed to support ________.
a) routine data cleaning tasks and integration
b) advanced query optimization
c) high-level management decision making
d) real-time transaction data processing
Que14. A retail chain stores customer transactions, loyalty card information, and E-commerce records in separate systems. Before generating a unified customer profile and analyzing their overall buying behaviour, the company must perform ________ to combine these different data sources into a single, consistent dataset.
a) Data cleaning
b) Data integration
c) Data transformation
d) Data reduction
Que15. According to the lecture, which of the following terms belongs to the “vocabulary of analytics”?
a) OLAP
b) Data warehousing
c) ETL and DSS
d) All the options given
Nptel Business Intelligence & Analytics Week 1 Answers (Jan-Apr 2025)
Course link: Click here
Que. 1) What does KDD stand for in the context of data mining?
a) Key Data Development
b) Knowledge Discovery from Data
c) Knowledge Data Design
d) Key Data Distribution
Que. 2) Which of the following does NOT belong to the data preparation phase?
a) Data cleaning
b) Data integration
c) Data visualization
d) Data selection
Que. 3) Which type of data is specifically classified as unstructured?
a) A table of employee records with defined columns.
b) Free-text comments collected from customer surveys.
c) Data logged in sequential order with timestamps.
d) Numerical data organized in a consistent matrix.
Que. 4) In real-world applications, data can often be a mixture of:
a) Only structured data
b) Only unstructured data
c) Structured, semistructured, and unstructured data
d) Structured and unorganized data
Que. 5) A car company has collected sales data, customer feedback, and production reports over the past five years in various formats. To analyze total sales by region and model across this period, the data must undergo __________ to consolidate, aggregate, and restructure it for meaningful analysis.
a) Data integration
b) Data normalization
c) Data transformation
d) Data cleaning
Que. 6) Which of the following is an example of how online platforms like Amazon enhance the long tail phenomenon discussed in the lecture?
a) Offering only best-selling items in stock.
b) Providing recommendations for less popular books based on user preferences.
c) Limiting the variety of products available for faster shipping.
d) Only stocking products that have been successful in physical stores.
Que. 7) As discussed in the lecture, in the context of analytics, which of the following terms best represents “DSS”?
a) Data Storage Systems
b) Digital Software Solutions
c) Decision Support Systems
d) Data Security Services
Que. 8) What does ETL stand for in the context of data management?
a) Extract, Transform, Load
b) Evaluate, Transfer, Load
c) Extract, Test, Load
d) Evaluate, Transform, Load
Que. 9) As discussed in the lecture, which of the following terms is NOT usually associated with the vocabulary of analytics?
a) Data Warehousing
b) Data Governance
c) Online Analytical Processing (OLAP)
d) Knowledge Discovery in Databases (KDD)
Que. 10) What is an outlier in a data set?
a) A data object that conforms to the general behavior of the data.
b) A data object that does not comply with the general behavior or model of the data.
c) A common occurrence within the data set.
d) A data point that represents average behavior.
Que. 11) Which of the following is an example of supervised learning?
a) Grouping data points into clusters based on inherent similarities.
b) Diagnosing diseases based on labeled medical data.
c) Discovering patterns in data without predefined categories.
d) Organizing items into groups based on unknown attributes.
Que. 12) What is the primary function of a data warehouse?
a) Increases the security of data
b) Integrates data from multiple sources
c) Optimizes search engine results
d) Analyzes data in real-time
Que. 13) In the context of business intelligence, what is the role of clustering?
a) To create data warehouses
b) To group customers based on their similarities
c) To enhance data visualization
d) To manage real-time data
Que. 14) How does data mining contribute to business intelligence?
a) By transforming raw data into meaningful information
b) By providing insights from historical and current data
c) By ensuring the security of sensitive data
d) By automating data storage processes
Que. 15) In the context of data mining, which of the following best describes the nature of relational databases?
a) They store highly structured data with predefined attributes and semantic meaning.
b) They store unstructured data such as images, audio, and text.
c) They dynamically adjust to various data types and structures without predefined constraints.
d) They are specifically designed for organizing large amounts of multimedia content.
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