NOTE: There are 11 Questions in all.
Question
1 is compulsory and carries 16 marks. Answer to Q. 1. must be written in the
space provided for it in the answer book supplied and nowhere else.
Answer
any THREE Questions each from Part I and Part II. Each of these questions
carries 14 marks.
Any
required data not explicitly given, may be suitably assumed and stated.
Q.1 Choose the correct or best alternative in the
following: (2x8)
a.
The
abundance of data in the present day society is a
(A)
data poor and information poor situation.
(B) data rich but information poor situation.
(C) data rich and information rich situation.
(D) data poor and information rich situation.
b.
Data
mining is a synonym for
(A)
DBMS. (B) RDBMS.
(C) KDD. (D) Statistical Analysis.
c. Data mining is a step in the
(A) Data cleaning. (B) Data transformation.
(C) Data selection. (D) knowledge discovery process.
d. A data mart is a
(A) data warehouse (B)
database
(C) subset of data warehouse (D) meta data
e. Operational databases do not typically
include
(A)
raw
data. (B) transaction data.
(C) historical
data. (D) indexing and hashing.
f. Principal component analysis is used in
(A)
data
reduction (B) data compression
(C) data cleaning (D) data pre-processing
g. Combining data from multiple sources into coherent data is termed as
(A) data cleaning. (B) data
integration.
(C) data transformation. (D) data clustering.
h. In the data warehouse environment.
(A) data is time variant.
(B) there is a firm set of requirements.
(C) transaction response time is a major
issue.
(D) development is done one application at a
time.
Answer
any THREE Questions. Each question carries 14 marks.
Q.2 a. Describe the evolution of Decision support
system. (7)
b. Explain with
reasons the crisis of data credibility in naturally evolving architecture. (7)
Q.3 a. Explain how data warehousing helps the
executives to make strategic decisions. (5)
b. Suppose that a data warehouse consists of the three
dimensions time, doctor and patient and two measures count and charge,
where charge is the fee that a doctor charges a patient for a visit. (9)
i) Draw a schema diagram for the above
warehouse, using one of three classes of schema.
ii) Enumerate based on the kind of aggregate functions that could be
used in a datacube.
Q.4 a. Explain how data cubes model n-dimensional
data. Give an example of a 3-D view of sales data of an electronics company
according to dimensions: time, item and location. (7)
b. Distinguish between snowflake schema and star schema model. (5)
c. What is Meta data? (2)
Q.5 a. Describe
the three tier architecture of data warehouse. (7)
b. What are the different data warehouse models from the architecture
point of view? (7)
Q.6 a. In a data warehouse technology, a multiple dimensional
view can be implemented by ROLAP or by MOLAP. For each of the technique mentioned
above, explain how each of the following functions are implemented. (7)
(i) Roll Up
(ii) Drill Down
b. Explain how data warehouse enables the EIS analyst to deal with
various management needs. (7)
Answer
any THREE Questions. Each question carries 14 marks.
Q.7 a. Describe various problems relating to the use
and storage of external and unstructured data in the data warehouse. (7)
b. Describe how
meta data is vital and important component of data warehouse. Also list
components of a typical meta data. (7)
Q.8 a. What are the various forms of data
pre-processing? Describe the purpose of data cleaning routines. How do you detect
outliers? (7)
b. What are NAIVE Bayesian
Classification Networks? Explain. (7)
Q.9 a. Define z-score normalization. Find the z-score
normalization value Rs. 73, 600
for income when the mean and the standard deviations for the attribute income
are Rs. 54000 and Rs.16, 000 respectively. (7)
b. Describe data
compression and discretization techniques. (5)
c. Data quality can be assessed in terms of accuracy,
completeness and consistency. Propose two
other dimensions of data quality. (2)
Q.10 a. What is
corporate data model? How this can be changed to task the data model into data
warehouse design. (7)
b. Describe Market
basket analysis as a form of association rule mining. (7)
b. What is a decision tree?
Write basic algorithm for inducing a decision tree from
training sampler.
(7)