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Data mining quiz no 1

Total questions: 50

Worksheet time: 50mins

Name
Class
Date
1.

Which is not a property of data warehouse?

a)

subject oriented

b)

time variant

c)

collection from heterogeneous sources

d)

volatile

2.

data warehousing used in_______________

a)

transaction system

b)

decision support system

3.

data warehouse is based on_____________

a)

two dimensional model

b)

three dimensional model

c)

multidimensional model

d)

unidirectional model

4.
What is a Data Mart?
a)
A data mart is a subgroup of the data warehouse
b)
A data mart is another type of data warehouse
c)
A data mart is not actually related to data warehouses
d)
None of these
5.

What is a subset of the data warehouse that is designed for a particular line of business?

a)

Data Structure

b)

Schema

c)

Data Mart

d)

Objects

6.

Which among the two is the modern approach that handles all the transformation in warehouse?

a)

ETL

b)

ELT

7.
What does OLTP stand for?
a)
Online transaction processing
b)
Offline transaction processing
c)
Outline trajectory processing
d)
Online traffic processing
8.

multidimensional model of data warehouse called as__

a)

data structure

b)

table

c)

data cube

d)

tree

9.

1. ____________ is the process of the discovering useful patterns and trends in large data set.

a)

Data Mining

b)

Data cleaning

c)

Data processing

d)

Data warehouse

10.

a data warehouse can include

a)

flat-files

b)

database table

c)

online data

d)

all

11.
The data is stored, retrieved & updated in ____________.
a)
OLAP.
b)
OLTP.
c)
SMTP.
d)
FTP.
12.

The full form of OLAP is

a)

Online Analytical Processing

b)

Online Advanced Processing

c)

Online Advanced Preparation

d)

Online Analytical Performance

13.
What do data warehouses support?
a)
OLAP
b)
OLTP
c)
OLAP and OLTP
d)
Operational databases
14.

The process of viewing the cross-tab (Single dimensional) with a fixed value of one attribute is

a)

Slicing

b)

Dicing

c)

Pivoting

d)

Both Slicing and Dicing

15.

On what is data warehouse based?

a)

1 D Model

b)

2 D Model

c)

3 D Model

d)

Multidimensional Model

16.

Identify the term used to define the multidimensional model of the data warehouse

a)

Table

b)

Tree

c)

Data Cube

d)

Data Structure

17.

Who is the father of data warehousing?

a)

Ralph Kimball

b)

Bill Inmon

c)

Barry Devlin

d)

None of the above

18.

What is another name for data mining?

a)

Information Retrieval Method

b)

Big Data Analysis

c)

Knowledge Discovery in Data

d)

Data Extraction Technique

19.

What is the process of finding potentially useful patterns from huge data sets called?

a)

Data Extraction

b)

Data Interpretation

c)

Data Analysis

d)

Data Mining

20.

Which technique is used to remove noise and inconsistent data in the data cleaning process?

a)

Clustering

b)

Regression

c)

Outlier Detection

d)

Binning

21.

What is the goal of data selection in data mining?

a)

To introduce noise into the dataset

b)

To remove all irrelevant data

c)

To increase the dataset size

d)

To ensure the dataset is representative and manageable

22.

What is the main responsibility of the Pattern Evaluation Modules in data mining architecture?

a)

Pattern Evaluation

b)

Data Integration

c)

Knowledge Presentation

d)

Data Cleaning

23.

What is the main challenge related to handling and processing large volumes of data in data mining?

a)

Data Scalability

b)

Data Uncertainty

c)

Data Noise

d)

Data Diversity

24.

What is the social impact of data mining known as when users are unaware of data collection?

a)

Privacy-Preserving Data Mining

b)

Invisible Data Mining

c)

Ethical Data Mining

d)

User Interaction Data Mining

25.

Which data mining technique is used to predict future trends based on historical data?

a)

Classification

b)

Clustering

c)

Regression

d)

Association

26.

What is the term for the process of extracting useful information from text data?

a)

Text Analysis

b)

Text Mining

c)

Text Extraction

d)

Text Interpretation

27.

Which data mining technique is used to find patterns that occur together in a dataset?

a)

Classification

b)

Clustering

c)

Regression

d)

Association

28.

What is the primary goal of data preprocessing in the data mining process?

a)

To increase data complexity

b)

To reduce data redundancy

c)

To improve data quality

d)

To decrease data volume

29.

Which data mining technique is used to group similar data points together?

a)

Classification

b)

Clustering

c)

Regression

d)

Association

30.

What is the term for the process of analyzing data to extract meaningful insights?

a)

Data Exploration

b)

Data Scrutiny

c)

Data Examination

d)

Data Inspection

31.

What is the primary purpose of data preprocessing in data mining?

a)

To transform raw data into an understandable format

b)

To analyze data patterns

c)

To visualize data

d)

To store data in databases

32.

Which of the following is NOT a measure of data quality?

a)

Complexity

b)

Completeness

c)

Accuracy

d)

Timeliness

33.

What technique is used to handle missing values in data?

a)

Data integration

b)

Data transformation

c)

Data cleaning

d)

Data reduction

34.

Which algorithm is widely used for finding frequent itemsets in a dataset?

a)

Support Vector Machine

b)

Decision Tree

c)

Apriori

d)

K-Means

35.

What does the term 'support' refer to in association rule mining?

a)

The strength of the association

b)

The likelihood of an item being purchased

c)

The percentage of transactions containing an item

d)

The total number of items in a dataset

36.

Which of the following is a disadvantage of the Apriori algorithm?

a)

Flexibility

b)

Ease of implementation

c)

High memory usage

d)

Simplicity

37.

What is the purpose of market basket analysis?

a)

To identify products that frequently co-occur in transactions

b)

To analyze customer demographics

c)

To optimize supply chain logistics

d)

To evaluate employee performance

38.

Which method is used in FP-Growth algorithm to represent frequent itemsets?

a)

Hash Table

b)

K-D Tree

c)

FP-tree

d)

Decision Tree

39.

What does normalization in data transformation aim to achieve?

a)

To integrate multiple data sources

b)

To reduce data volume

c)

To scale data within a specified range

d)

To eliminate duplicates

40.

Which of the following is an example of a positive correlation?

a)

As temperature increases, ice cream sales decrease

b)

As price increases, demand decreases

c)

As study time increases, exam scores increase

d)

As age increases, physical activity decreases

41.

What is the main goal of data mining?

a)

To extract useful information from large datasets

b)

To store data securely

c)

To visualize data trends

d)

To clean data for analysis

42.

Which of the following techniques is commonly used for data visualization?

a)

Regression Analysis

b)

Clustering

c)

Bar Charts

d)

Data Warehousing

43.

What does the term 'overfitting' refer to in machine learning?

a)

When a model performs well on training data but poorly on unseen data

b)

When a model is too simple to capture the underlying trend

c)

When a model is trained on too little data

d)

When a model is unable to learn from the data

44.

What is the purpose of clustering in data analysis?

a)

To group similar data points together

b)

To predict future trends

c)

To reduce data dimensionality

d)

To visualize data distributions

45.

Which of the following is a common technique for dimensionality reduction?

a)

Principal Component Analysis (PCA)

b)

Linear Regression

c)

Support Vector Machines

d)

Random Forest

46.

What is the purpose of feature selection in machine learning?

a)

To reduce the number of input variables

b)

To increase the model complexity

c)

To visualize data relationships

d)

To enhance data storage

47.

Which of the following is a common method for evaluating the performance of a classification model?

a)

Confusion Matrix

b)

Data Normalization

c)

Data Integration

d)

Data Transformation

48.

What does the term 'bias' refer to in the context of machine learning?

a)

The error due to overly simplistic assumptions in the learning algorithm

b)

The error due to noise in the training data

c)

The error due to insufficient training data

d)

The error due to model complexity

49.

Which of the following methods is used for association rule mining?

a)

Random Forest

b)

Apriori Algorithm

c)

Neural Networks

d)

Support Vector Machines

50.

What is the main objective of data cleaning in data mining?

a)

To remove inaccuracies and inconsistencies in data

b)

To visualize data trends

c)

To store data efficiently

d)

To analyze data patterns