Master of Computer Application II (Computer Science)
Examination: Oct Nov 2016 Semester IV (Old CGPA)
SLR No. Day
Date Time Subject Name Paper
No. Seat No.
SLR U
-32
Saturday
19/11/2016
02.30 PM
to
05.00 PM
Data Mining and
Warehouse
C

Instructions: Question no. 1 2 are compulsory
Attempt any three questions from Q. No. 3 to Q. No. 7
Figures to the right indicate full marks.
Total Marks: 70
Q.1 Choose correct alternatives 10
The partitions of overall data warehouse is
Database data cube
data mart operational data
Which of the following is/are the Data mining tasks?
Classification Association clustering
interface of associative rules all of the above
In K-nearest neighbor algorithm K stands for
number of neighbors that
are investigated
number of interactions
number of total records random number
Data mining is used to aid in
operational management analyzing past decision
made by managers
detecting patterns in
operational data
retrieving archival data
KDD describes the
whole process of extraction
of knowledge from data
extraction of data
extraction of information extraction of rules
An OLAP tool provides for
multidimensional analysis Roll-up and drill-down
slicing and dicing Rotation
Which of the following statement is true?
A fact table describes the
transaction stored in a DWH
the fact table of a data
warehouse is the main store
of descriptions of the
transactions stored in a
DWH
The fact table of a data
warehouse is the main store
of all of the recorded
transactions over time.
a fact table maintains the
old records of the database
Page 1 of 2
The type of relationships in star schema is
Many-to-many one-to-one
one-to-many many-to-one
The next stage to data selection in KDD
Enrichment coding
cleaning reporting
10) The partition of overall data warehouse is
database Data Cube
data mart operational data
State true or false 04
The Synonym for data mining is OLAP.
OLTP stands for online Transaction Processing.
OLAP manages both current and historic transactions.
Data mining is used to refer discovery stage in knowledge discovery in
database.
Q.2 write a short notes on
Data Marts
Data Cube
08
Answer the following 06
Describe data reduction technique.
What is data mining?
Q.3 Answer the following 14
What is cluster analysis? Explain types of data in cluster analysis.
Differentiate between OLTP an OLAP.
Q.4 Answer the followings 14
Explain snowflake and fact constellation schema model with example.
Explain different applications of data mining.
Q.5 Answer the followings 14
Discuss different OLAP Operations.
Explain agglomerative and divisive hierarchical method of clustering
Q.6 Answer the following 14
Explain in detail decisions tree induction method.
Describe the issues regarding classification and prediction.
Q.7 Answer the following 14
Explain data warehouse architecture.
Explain K medoids method.