1.What does KDD stand for in the context of data mining?
Key Data Development
Knowledge Discovery from Data
Knowledge Data Design
Key Data Distribution
2.Which of the following does NOT belong to the data preparation phase?
Data cleaning
Data integration
Data visualization
Data selection
3.Which type of data is specifically classified as unstructured?
A table of employee records with defined columns.
Free-text comments collected from customer surveys.
Data logged in sequential order with timestamps.
Numerical data organized in a consistent matrix.
4.In real world applications, data can often be a mixture of:
Only structured data
Only unstructured data
Structured, semistructured, and unstructured data
Structured and unorganized data
Data integration
Data normalization
Data transformation
Data cleaning
6.Which of the following is an example of how online platforms like Amazon enhance the long tail phenomenon discussed in the lecture?
Offering only best-selling items in stock.
Providing recommendations for less popular books based on user preferences.
Limiting the variety of products available for faster shipping.
Only stocking products that have been successful in physical stores.
7.As discussed in the lecture, in the context of analytics, which of the following terms best represent to "DSS"?
Data Storage Systems
Digital Software Solutions
Decision Support Systems
Data Security Services
8.What does ETL stand for in the context of data management?
Extract, Transform, Load
Evaluate, Transfer, Load
Extract, Test, Load
Evaluate, Transform, Load
9.As discussed in the lecture, which of the following terms is NOT usually associated with the vocabulary of analytics?
Data Warehousing
Data Governance
Online Analytical Processing (OLAP)
Knowledge Discovery in Databases (KDD)
10.What is an outlier in a data set?
A data object that conforms to the general behavior of the data.
A data object that does not comply with the general behavior or model of the data
A common occurrence within the data set.
A data point that represents average behavior.
11.Which of the following is an example of supervised learning?
Grouping data points into clusters based on inherent similarities.
Diagnosing diseases based on labeled medical data.
Discovering patterns in data without predefined categories.
Organizing items into groups based on unknown attributes
12.What is the primary function of a data warehouse?
Increases the security of data
Integrates data from multiple sources
Optimizes search engine results
Analyzes data in real-time
13.In the context of business intelligence, what is the role of clustering?
To create data warehouses
To group customers based on their similarities
To enhance data visualization
To manage real-time data
14.How does data mining contribute to business intelligence?
By transforming raw data into meaningful information
By providing insights from historical and current data
By ensuring the security of sensitive data
By automating data storage processes
15.In the context of data mining, which of the following best describes the nature of relational databases?
They store highly structured data with predefined attributes and semantic meaning
They store unstructured data such as images, audio, and text.
They dynamically adjust to various data types and structures without predefined constraints.
They are specifically designed for organizing large amounts of multimedia content.