Download CUSTOMER_CODE SMUDE DIVISION_CODE SMUDE

CUSTOMER_CODE
SMUDE
DIVISION_CODE
SMUDE
EVENT_CODE
APR2016
ASSESSMENT_CODE MCA5043_APR2016
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
11567
QUESTION_TEXT
List the objectives of data mining in telecommunication.
SCHEME OF
EVALUATION
1.Helps to understand the business involved, identify
telecommunication patterns, catch fraudulent activities, make better use
of resources and improve the quality of service.
2.Algorithms include CART, c4.5, neural networks and Bayesian
classifiers among others.
3.The ability to handle noise in this case is obviously critical to the
successful application of data mining algorithms.
4.The company’s face the problem of churning.
5.Data mining is one solution to do appropriate credit scoring and to
combat churns in the telecom industry.
6.Used to churn analysis to perform 2 key tasks: Predict and
Understand.
7.Decision support in telecommunication forms the rules that can be
used as decision support rules.
8.In central system RTKP procedure based on conjunctive and
disjunctive matrices and operators.
9.KDD has delivered a variety technique to discover patterns from vast
amount of data which helps in mining for complex data.
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
11572
QUESTION_TEXT
Explain various characteristics of data warehouse?
1.Subject oriented
2.Integrated
SCHEME OF EVALUATION 3.Non Volatile
4.Time variant
(2.5 marks each)(10 marks)
QUESTION_T
DESCRIPTIVE_QUESTION
YPE
QUESTION_ID 72810
QUESTION_T
Differentiate between OLTP and Data Warehouse.
EXT
Application databases are OLTP systems where every transaction has to be
recorded as and when it occurs. A Data Warehouse on the other end is a
database that is designed for facilitating querying and analysis. (1 mark)
OLTP VS Data Warehouse:
SCHEME OF
EVALUATION
(9 marks)
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
72812
QUESTION_TEXT
What is Data Loading in Data Warehouse? Explain different types of
Data Loading.
SCHEME OF
EVALUATION
Data Loading implies physical movement of the data from the
computer(s) storing the source database(s) to that which will store the
data warehouse database, assuming it is different. (1 mark)
Data Loading Types:
Initial Load: (3 marks)
Populating all the Data Warehouse tables for the very first time.
Creation of indexes on initial loads or full refreshes requires special
consideration. Index creation on mass loads can be too timeconsuming. So drop the indexes prior to the loads to make the loads go
quicker. You may rebuild or regenerate the indexes when the loads are
complete.
Incremental Load: (3 marks)
Applying ongoing changes as necessary in a periodic manner. These are
the application of ongoing changes from the source systems. Changes
to the source systems are always tied to specific times, irrespective of
whether or not they are based on explicit time stamps in the source
systems.
Full Refresh: (3 marks)
Completely erasing the contents of one or more tables and reloading
with fresh data. This type of application of data involves periodically
rewriting the entire Data Warehouse. Sometimes partial refreshes also
requires rewriting only specific tables. Partial refreshes are rare because
every dimension table is intricately tied to the fact table. As far as the
data application modes are concerned, full refresh is similar to the
initial load. However in the case of full refreshes, data exists in the
target tables before incoming data is applied.
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
126112
QUESTION_TEXT
Explain briefly
a. Hierarchical clustering
b.
Divisive clustering
SCHEME OF EVALUATION
a.
b.
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
126114
QUESTION_TEXT
Hierarchical clustering (5 marks)
Divisive clustering (5 marks)
Discuss the following data warehouse schema
a. Star schema
b.
Snowflake schema
a.
Star schema (5 marks)
b.
Snowflake schema (5 marks)
SCHEME OF EVALUATION