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Data Mining Quiz

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

Which of the following best describes Data Mining?

a)

Storing large volumes of data

b)

Extracting useful patterns and knowledge from data

c)

Querying a database using SQL

d)

Visualizing data using charts

2.

Which sequence correctly represents the Knowledge Discovery in Databases (KDD) process?

a)

Data Mining → Data Warehouse → Database → Decision

b)

Database → Data Mining → Data Warehouse → Decision

c)

Database → Data Preprocessing → Data Mining → Evaluation

d)

Data Mining → Database → Preprocessing → Knowledge

3.

Which statement correctly differentiates a Database and a Data Warehouse?

a)

Both store only historical data

b)

Database supports analysis; Data warehouse supports transactions

c)

Database stores current data; Data warehouse stores integrated historical data

d)

Database is read-only; Data warehouse allows updates

4.

Where does a Data Cube fit in the data mining architecture?

a)

Inside the operational database

b)

Directly on raw transactional data

c)

Built from the data warehouse for OLAP analysis

d)

Used only for classification

5.

Which OLAP operation moves from summarized data to more detailed data?

a)

Roll-up

b)

Slice

c)

Dice

d)

Drill-down

6.

Which of the following is an example of Invisible Data Mining?

a)

Running Apriori algorithm in SAS

b)

Writing SQL queries for reports

c)

Google automatically ranking search results

d)

Designing a star schema

7.

In which data mining functionality are predefined class labels required?

a)

Clustering

b)

Association

c)

Classification

d)

Outlier detection

8.

Identifying unusual credit card transactions is an example of:

a)

Classification

b)

Association analysis

c)

Clustering

d)

Outlier analysis

9.

Grouping genes with similar expression patterns in microarray data uses which functionality?

a)

Classification

b)

Clustering

c)

Trend analysis

d)

Discrimination

10.

Which of the following is considered a major challenge in data mining?

a)

Small data size

b)

Single data source

c)

Poor data quality and noise

d)

Simple interpretation of results