Business Intelligence & Analytics Week 1 Nptel Answers
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Nptel Business Intelligence & Analytics Week 1 Answers (Jan-Apr 2025)
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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