1.
What
is Data Mining? Goal of Data Mining and application of Data Mining.
2.
What
kinds of data on Data Mining?
3.
Classification
of Data Mining.
4.
Give
some alternative terms for Data Mining.
5.
Define
each of the following Data Mining Functionalities: Characterization,
discrimination, association and correlation analysis, classification, prediction,
clustering and evolution analysis.
6.
List
major issues in Data Mining system.
7.
Describe
the difference between the following approaches for integration of data mining system
with a database or data warehouse system: No coupling, loose Coupling,
Semitight coupling, Tight Coupling.
8.
What
are the Steps involved in KDD Process?
9.
Describe Challenges to Data Mining regarding
data Mining Methodology and User Interaction issues.
10.
Describe
Challenges to data Mining Regarding Performance Issues.
11.
How
Data warehouse different from database? How are they Similar?
12.
What
is Query driven approaches and Update driven approaches which one is used by
data warehouse?
13.
What
makes a Pattern Interesting?
14.
Explain
architecture of Data Mining.
15.
How
is the Derived Model Presented?
16.
What
is Cluster Analysis?
17.
What is Descriptive and Predictive Mining?
18.
Difference
between OLAP and OLTP
19.
Evolution
of Database system Technology.
20.
Discuss
the role of data mining in data warehousing.
21.
What
is Spatial, Sequence Mining?
22.
What
is Text and Web Mining?
23.
What
is the difference between discrimination and classification?
24. What is the
difference between classification and prediction?
25. What is mean by
Pattern?
26.
