Thursday, 15 December 2016

mit401 smu msc it fall 2016 (jan/feb 2017 exam) IVth sem assignment

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PROGRAM
Master of Science in Information Technology(MSc IT)
SEMESTER
FOURTH
SUBJECT CODE & NAME
MIT401– Data Warehousing and Data Mining
Qus:1 Define data warehouse. Differentiate between OLTP and data warehouse.
Answer: Data Warehouses and Data Warehouse applications are designed primarily to support executives, senior managers, and business analysts in making complex business decisions. Data Warehouse applications provide the business community with access to accurate consolidated information from various internal and external sources. The goal of using a Data Warehouses to have an efficient way of managing information and analyzing data. Now day’s


Qus:2 What is schema? List the name of data warehouse schemas and explain Snowflake schema.
Answer: A schema is a collection of database objects, including tables, views, indexes, and synonyms. There are three schemas existed to define Data Warehouse,
 Star Schema
 Snowflake Schema
 Fact-



Qus:3 What is Metadata? Explain technical and operational metadata.
Answer: Since the early 1990s, data warehouses have been at the forefront of information technology applications as a way for organizations to effectively use digital information for business planning and decision-making. Data warehouses are computer based information


Qus:4 Explain data mining and knowledge discovery process.
Answer: Data Mining is not specific to any industry – it requires intelligent technologies and the willingness to explore the possibility of hidden knowledge that resides in the data. Data Mining is also referred to

Qus:5 Briefly describe K-means method for clustering. List its advantages and drawbacks.
Answer: K-means (Mac Queen, 1967) is one of the simplest unsupervised learning algorithms that solve the well-known clustering problem. The procedure follows a simple and easy way to classify a given data set through a certain number of clusters (assume k clusters) fixed a priori. The main idea is to define k cancroids, one for each cluster.
The basic step of k-means clustering is simple. In the beginning, we determine number of cluster K and we



Qus: 6 Explain how Data Mining is useful for following:
(a) Targeted marketing.
(b) Telecommunications.
Answer: (a) Targeted marketing.
Insurance and direct mail are two industries that rely on data analysis to make profitable business decisions. For example, insurers must be able to accurately assess the risks posed by their policyholders to set insurance premiums at competitive levels. For example, overcharging low


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