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PROGRAM-MCA(Revised
Fall 2012)
SEMESTER-V
SUBJECT
CODE & NAME-MCA5043– Data Warehousing and Data Mining
CREDIT-4
BK
ID-B1633
MAX.
MARKS-60
Q1.
Explain the Top-Down and Bottom-up Data
Warehouse development Methodologies.
Answer:
Bottom-up design
Ralph Kimball, a well-known
author on data warehousing, is a proponent of an approach to data
warehouse design which he describes as bottom-up.
In the bottom-up
2. Explain the
Functionalities and advantages of Data Warehouses.
Answer:
Data
Warehousing
Data
warehouse is defined as "A subject-oriented, integrated, time-variant, and
nonvolatile collection of data in support of management's decision-making
process."
In
this definition the data is:
•
Subject-oriented as the warehouse is organized around the major subjects of the
enterprise (such as customers, products, and sales)
3.
Describe about Hyper Cube and Multicube 5+5
Answer.
Hyper Cube and Multicube
Multidimensional
databases can present their data to an application using two types of cubes: hypercubes and multicubes.
4.
List and explain the Strategies for data reduction. 5*2
Answer.
Strategies for data reduction
Data reduction:
Obtain a reduced representation of the data set that is much smaller in volume
but yet produces the same (or almost the
5.
Describe K-means method for clustering. List its advantages and drawbacks. 5+5
Answer.
K-means method for clustering
k-means clustering is
a method of vector quantization, originally from signal processing, that is
popular for cluster analysis in data mining. k-means clustering aims to
partition n observations into k clusters in which each observation
6.
Describe about Multilevel Databases and Web Query Systems 5+5
Answer.
Multilevel Databases and Web Query Systems
Multilevel
Databases
A multilevel database
system (MDBMS) supports the application of a multilevel policy for regulating
access to the database objects. In this approach at the bottom level database
the semi structured data is stored in web repositories as hyper text .The generalizations are
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