IT446 Data Mining and Data Warehousing

IT446

Assignment 2

Deadline: Saturday 04/11/2017 @ 23:59

[Total Mark for this Assignment is [5]

College of Computing and Informatics

Question One

Learning Outcome(s):

Student differentiate between different data warehouse models and forms, Data forms, and OLTP and OLTP

1 Mark

Compare the following with the help of examples.

(a) Star schema and snowflake schema

(b) Data cleaning and data transformation


(c) Enterprise warehouse, data mart, and virtual warehouse

(d) OLAP and OLTP

Question Two

1 Mark

Learning Outcome(s):

Student know three-tire data warehouse, data cube concept, understand data cube computation.

a) Explain three tiers of data warehouse architecture.

b) Which methods are used for efficient computations of data cubes.

c) Which algorithm is most appropriate to compute closed iceberg cubes efficiently?

Question Three

2 Marks

Learning Outcome(s):

Instructors: State the Learning Outcome(s) that match this question

Consider the database containing transaction data as stated in the table below. Use Apriori algorithm to find frequent item sets where minimum support is 50%.

Question Four

1 Mark

Learning Outcome(s):

Instructors: State the Learning Outcome(s) that match this question

Discuss candidate generation in Generalized Sequential Pattern (GSP) with the help of an example.