Mumbai University Question Bank
for Bachelor of Science (B.Sc.)
Information Technology - Semester 6
Question Bank Business Intelligence
Unit
– 1
Q.1 What is
Business Intelligence? Why Effective and timely decisions are must?
Q.2 What are
the benefits of business intelligence system?
Q.3 Define the
terms: i) Data ii) Information iii) Knowledge
Q.4 Explain
the role of mathematical models.
Q.5 Explain
business intelligence architecture
Q.6 What are
the main components of business intelligence system? Explain
Q.7 Explain
the Cycle of a business intelligence analysis.
Q.8 What are
the factors in business intelligence projects?
Q.9 Explain
the phases in the development of business intelligent system
Q.10 What is
the relationship between Ethics and Business Intelligence.
Q.11 Define
Decision Support Systems.Explain representation of the decision-making process
Q.12 Define
System
Q.13 Explain
logical flow of problem solving process
Q.14 What are
the factors that influence a rational choice?
Q.15 Explain
logical structure of decision making process
Q.16 Explain
Phases of decision – making process.
Q.17 What are
the different Types of decisions?
Q.18 What are
the different Types of decisions based on their nature? Explain
Q.19 What are
the different Types of decisions based on their scope? Explain
Q.20 What are
the characteristics of information in terms of scope of decisions?
Q.21 Explain
different approaches to the decision-making process.
Q.22 Explain
different types of rational approach.
Q.23 Write
short note on Evolution of information systems
Q.24 Explain
structure of a decision support system
Q.25 What are
the relevant features of a DSS?
Q.26 Explain
extended structure of a decision support system
Q.27
Differentiate between structure and extended structure of a decision support
system
Q.28 What are
the advantages of DSS?
Q.29 Explain
different development phases of DSS.
Q.30 What are
the factors that affect the degree of success of a DSS?
Unit – II
Q.1 What do
you mean by model?
Q.2 What are
the different types of models?
Q.3 What are
the different types of model based on their nature?
Q.4 What are
the different types of model based on temporal dimension?
Q.5 How you
develop a model OR phases of model?
Q.6 What are
the factors & influence choice of model?
Q.7 What are
the main categories of mathematical model OR the different classes of model?
Q.8 What are
the different categories of predictive model?
Q.9 What is
data mining?
Q.10 How do
data mining activity sub-divided?
Q.11 What are
the steps in the development of data mining models OR Recurring steps in data
mining?
Q.12 What are
the difference between OLAPS statistic & data mining?
Q.13 How
attributes are categorized in data set?
Q.14 What are
the applications of data mining?
Q.15 What are the main phases
of data mining process?
Q.16 What are the professional
role in order to achieve an effective data mining process?
Q.17 What are the basic data
mining task? OR What are the seven basic data mining task? OR How you identify
data mining task?
Q.18 Who are the actors &
roles in data mining process?
Q.19 What do you mean by data
validation?
Q.20 How do quality input data
unsatisfactory?
Q.21 How you can correct
incomplete data? OR What are the different technique?
Q.22 How do data affected by
out layers?
Q.23 What do you mean by
standardization of data OR different methods of normalization of data?
Q.24 Write short note on
feature extraction?
Q.25 What are the main criteria
to determine whether a data reduction technique should use?
Q.26 What is sampling? What are
the different types of it?
Q.27 What is the purpose of
feature selection or reduction?
Q.28 What are the different
types of myopic search scheme that can be followed?
Q.29 What is PCA?
Q.30 What do
you mean by data discretization?
Unit – III
Q.1 What is the structure of
the learning process for classification ?
Q.2 What are the phases of
classification model OR three main phases of classification ?
Q.3 What are the categories of
classification model? Taxonomy of classification.
Q.4 How you evaluate
classification model?
Q.5 Write short note on to
Holdout method.
Q.6 Write short note on to
Repeated random sampling.
Q.7 Write short note on
Cross-Validation method.
Q.8 Write short note on
Confusion Matrices.
Q.9 Write short note on ROC
curve charts.
Q.10 Write short note on
Cumulative gain and Lift Charts.
Q.11 Explain Bayesian Algorithm
with the help of example.
Q.12 Write short note on Naïve
Bayesian Classification.
Q.13 Explain Bayesian Network.
Q.14 Short note on Logistic
Regression.
Q.15 Define Neural Network.
Q.16 Short note on Support
vector machine.
Q.17 What are the drawbacks of
imperial risk minimization?
Q.18 What you mean by
clustering?
Q.19 What are the requirements
of clustering methods?
Q.20 Taxonomy of clustering
methods.
Q.21 Short note on affinity
methods.
Q.22 Short note on partition
method.
Q.23 Short note on K-Means
Q.24 Short note on K-Mediode
Q.25 Write a short note on
Hierarchical methods.
Q.26 What are the types of
Hierarchical methods?
Q.27 Write a short note on
Agglomerative algorithm.
Q.28 Write a short note on divisive algorithm.
Unit – V
Q.1 Define Knowledge
Management.
Q.2 Explain relationship
between data, Information and Knowledge
Q.3 What are the
characteristics of knowledge?
Q.4 What are the differences
between Explicit and Tacit knowledge?
Q.5 Give the taxonomy of
knowledgeQ.6 Write short note on organizational learning and transformation
Q.7 What are the possible
reasons that people do not like to share knowledge?
Q.8 Why do companies need
knowledge management initiatives?
Q.9 Describe the process of
knowledge creation.
Q.10 What are the
characteristics of knowledge sharing?
Q.11 Define knowledge seeking
(sourcing)?
Q.12 What are the approaches to
knowledge management?
Q.13 Define knowledge
repository and describe how to create one.
Q.14 Explain KMS cycle
Q.15 What are knowledge
management technologies and their impact on web?
Q.16 What are the technologies
that support knowledge management?
Q.17 Define knowware
Q.18 Describe the major
categories of knowledge management tools
Q.19 Describe tools for
knowledge harvesting
Q.20 List the major systems
that are frequently integrated with KMS.
Q.21 Describe the role of CKO
Q.22 What are the principles
for designing successful COP?
Q.23 How communities of
Practice add value to an organization?
Q.24 What are the keys to KM
success for customer service?
Q.25 What are KM myths?
Q.26 What are knowledge
management traps?
Q.27 What are the drawbacks of
KMS?
Q.28 List some financial
(tangible) metrics of knowledge management.
Q.29 List some non- financial
(in tangible) metrics of knowledge management.
Q.30 Define Artificial
Intelligence
Q.31 What are the
characteristics of AI?
Q.32 What are the stages of AI
Evolution?
Q.33 Differentiate between AI
and natural intelligence
Q.34 What are the disciplines
and applications of AI?
Q.35 Define Expert System? What
are the features of Expert Systems?
Q.36 Differentiate between
Conventional systems and Expert Systems
Q.37 Differentiate between
Human Experts and Expert Systems
Q.38 What are the applications
of Expert Systems?
Q.39 What are the areas for
expert systems?
Q.40 Explain the structure of
expert system.
Q.41 Define Knowledge
engineering. What are the major activities in knowledge engineering?
Q.42 What are the difficulties
in acquiring knowledge?
Q.43 What are the advantages
and shortcomings of using multiple experts?
Q.44 Explain how expert system
perform inference?
Q.45 Describe the reasoning
procedures of forward chaining and backward chaining.
Q.46 What are the problem areas
suitable for expert systems?
Q.47 What are the generic
categories of expert systems?
Q.48 How to develop an expert
system?
Q.49 What are the benefits of
expert system?
Q.50 What are the problems and limitations of expert system?
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