BBIT 300 BIT 3201 DATA WAREHOUSING AND DATA MINING . KCA Past Paper

FACULTY OF COMPUTING AND INFORMATION MANAGEMENT
BACHELOR OF SCIENCE/BUSINESS IN INFORMATION TECHNOLOGY
BBIT 300 BIT 3201 DATA WAREHOUSING AND DATA MINING
DISTANCE LEARNING
DATE: JULY.2016 TIME: 2 HOURS
INSTRUCTIONS: Answer question ONE and any other TWO

QUESTION ONE [30 MARKS]
a) Describe the following concepts associated with data mining and data warehousing.
i. Granularity
ii. Data visualization
iii. Data mining
iv. OLAP
[4 Marks]
b) Briefly explain FIVE reasons for monitoring the usage of data warehouse data
[5 Marks]
c) Given databases of sufficient size and quality, data mining technology can generate new business
opportunities by providing two major capabilities. State and explain these capabilities.
[6 Marks]
d) Briefly explain the any FIVE data mining techniques:
[5 Marks]
e) Describe the general steps of data mining.
[7 Marks]
f) Explain the THREE properties of data in a data warehouse.
[3 Marks]
QUESTION TWO [20 MARKS]
a) The following documents were retrieved from a certain retail shop in town. Each document details the
contents of the shopping basket for eight (8) different customers.

Required:
i. Calculate the support for {Soda, Bread, Fruit}.
[3 Marks]
ii. Calculate the support count for {Soda, Bread, Fruit}.
[3 Marks]
iii. Find association rules, given min_support = 50% and the database of transactions:
[4 Marks]
b) State and explain the FIVE components of a data warehouse.
[10 Marks]
QUESTION THREE [20 MARKS]
A multidimensional database (MBD) is defined as a type of database that is optimized for data
warehouse and online analytical processing (OLAP) applications. Multidimensional databases
are frequently created using input from existing relational databases. In this respect:
a) Describe the following OLAP operations.
i. Roll-up
ii. Slicing
iii. Dicing
iv. Pivoting
[8 Marks]
b) Discuss the following schemas of a data warehouse.
i. Constellation schema
ii. Star schema
iii. Snowflake schema
[9 Marks]
c) Discuss the use of MOLLAP servers, in multidimensional databases.
[3 Marks]
QUESTION FOUR [20 MARKS]
a) Discuss any FIVE potential applications of data mining.
[5 Marks]
b) Explain the difference between data mining and OLAP.
[3Marks]
c) Differentiate between conceptual clustering and distance based clustering.
[4 Marks]
d) Discuss any FOUR challenges facing clustering as a data mining technique.
[8 Marks]
QUESTION FIVE [20 MARKS]
a) Using a well labeled diagram, describe the architecture of a data mining system.
[8 Marks]
b) Discuss what is meant by the following terms when describing multidimensional databases,
giving example in each case.
i. Dimension
ii. Dimensional table
iii. Fact
iv. Fact table
[8 Marks]
c) Explain FOUR differences between a data warehouse and a data mart.
[4 Marks]

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