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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
1.
Explain the Functionalities and advantages of Data Warehouses. 5+5
Answer.
Functionalities and advantages of Data Warehouses
Functionalities
A
data warehouse functions as a repository for all the data held by an organisation.
The main functions are to reduce cost of data storage, facilitate data mining,
and facilitate ability to back up data at an organisational level. A data warehouse is the main repository of an
organization's historical data, its corporate memory. A data warehouse is a
2
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 information that is in the Data Warehouse
is stored in a way that allows it to be connected to objects or event, which
occur in reality. Another characteristic that is frequently seen in Data Warehouses
is called Time Variant. A time variant Data Warehouse will allow changes in the
information to be monitored and recorded over time. All the programs that are
used by a
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 same) analytical results.
Why data reduction? —
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 belongs to
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
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