M.C.A.(Science) (Semester IV) (CBCS) Examination, 2017
DATA MINING AAND WAREHOUSE
Day Date: Friday, 21-04-2017 Max. Marks: 70
Time: 02.30 PM to 05.00 PM
N.B.: Question 1 and 2 are compulsory.
Attempt any Three from Q.3 to Q.7
Figures to the right indicate full marks.
Q.1 Choose the correct alternatives: 10
An system is market oriented.
OLAP OLTP OLEP None of these
An collect all the information about subject spanning the
Entire organization.
Virtual warehouse Data mart
Enterprise warehouse None of these
which detects errors in the data and rectifies them when
possible.
Data extraction Data cleaning
Load Refresh
The schema, is a variant of the star schema model,
Where some dimension tables are normalized, thereby further
splitting the data into additional tables.
Fact constellation snowflake
star None of these
It navigates from less detailed data to more detailed data.
Slice Dice Rotate Drill-down
is a summarization of the general characteristics or
features of a target class of data.
Data Characterization Data Classification
Data discrimination Data selection
The out put of KDD is
Data Information Query Useful information
Which of the following is not a kind of data warehouse
application?"
Information processing Analytical processing
Page 2 of 2
Data mining Transaction processing
describes the data contained in the data warehouse.
Relational data Operational data
Metadata Informational data
10) The star schema is composed of fact table.
One Two Three four
State whether the following statement is True or False: 04
The snowflake schema is a variant of the star schema model,
where some dimension tables are normalized.
Data Integration is not the process of combining multiple data
Sources
A data mining task can be specified in the form of a data-mining
Query, which is input to the data mining system
Bayesian classifiers are statistical classifiers.
Q.2 Write short note on the following: 08
Drill-down operation
Data cleaning as a process
Attempt the following: 06
Explain divisive hierarchical clustering method with example
Define Data mining? Explain the new trends in data mining
Q.3 Attempt the following: 14
What is data Data warehouse? Explain the difference between OLTP
and OLAP.
Explain different forms of multidimensional data model.
Q.4 Attempt the following: 14
What is association rule? Explain the use of market basket analysis
with example
State and explain data mining primitives with suitable example
Q.5 Attempt the following: 14
Explain the procedure of Back propagation method in detail.
State and explain the steps in k-medoids algorithm
Q.6 Attempt the following: 14
What is classification? Explain the steps in decision tree induction
method.
Explain various data mining applications.
Q.7 Attempt the following: 14
What is Cluster analysis? Explain Density-based clustering method
with example.
Explain the features of data mining query language.