Data Mining and Data Warehousing Question 1 Compare the following with the help
ID: 3604382 • Letter: D
Question
Data Mining and Data Warehousing
Question 1
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
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Question 2
Explain three tiers of data warehouse architecture.
Which methods are used for efficient computations of data cubes.
Which algorithm is most appropriate to computeclosed iceberg cubes efficiently?
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Question 3
Consider the database containing transaction data as stated in the table below. Use Apriori algorithm to find frequent itemsets where minimum support is 50% and minimum confidence is 50%.
Transactions
Item Set
I1
A,B,C
I2
A,C
I3
A,D
I4
B,E,F
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Question 4
Discuss candidate generation in Generalized Sequential Pattern (GSP) with the help of an example.
Transactions
Item Set
I1
A,B,C
I2
A,C
I3
A,D
I4
B,E,F
Explanation / Answer
Question 1:
(a) Star schema and snowflake schema:
Differences:
(b) Data cleaning and data transformation
Data cleaning is nothing but the process of finding errors in the data and finding solutions to them when possible.While Data transformation is the process of converting data from heterogeneous to semantics.
(c) Enterprise warehouse, data mart,and virtual warehouse
Enterprise warehouse, data mart,and virtual warehouse are three types of data warehouse models.
(d) OLAP and OLTP
The main difference between OLAP and OLTP is that online Analytical Processing that is designed to answer multi-dimensional queries, whereas as online Transaction Processing is mainly designed to manage business applications. Generally OLAP is customer-oriented and OLTP is business oriented.
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