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PROGRAM
MCA(Revised Fall 2012)
SEMESTER
V
SUBJECT CODE & NAME
MCA5043– Data Warehousing and Data Mining
1 Explain the
Top-Down and Bottom-up Data Warehouse development Methodologies.
Answer: Despite the fact that Data
Warehouses can be designed in a number of different ways, they all share a
number of important characteristics. Most Data Warehouses are Subject Oriented.
This means that the
2 Differentiate
E-R modeling and Dimensional Modeling
Answer: E - R Modeling
Entity - Relationship modeling is a very
popular method for designing databases. E-R modeling, as it is often called,
may be described as a topdown approach, in that it encourages looking at the
“big picture" first. We begin by describing the world in terms of entity
types that are related to one another in various
3 What is
repository? How is it helpful to the data warehouse maintenance?
Answer: A Data Mart is a repository
of data gathered from operational data and other sources that is
4 List and
explain the Strategies for data reduction.
Answer: Data reduction techniques
can be applied to obtain a reduced representation of the data set that is much
smaller in volume, yet closely maintains the integrity of the original data.
That is, mining on the reduced data set should be more efficient yet produce
the same (or almost the same)
5 Describe
K-means method for clustering. List its advantages and drawbacks.
Answer: K-means (MacQueen, 1967) is
one of the simplest unsupervised learning algorithms that solve the well known
6 Explain how
Data Mining is useful in telecommunications.
Answer: The following are a few
topics where data mining improve telecommunication services.
Multidimensional
Analysis of Telecommunication Data: Telecommunication data are intrinsically with
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