Elective - Data Warehousing & Data mining

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Case Study Project

Total Marks: 100

Elective -  Data Warehousing & Data mining

Question. 1. Discuss on the design and implementation of data warehouse as well as the use of data mining algorithms for the purpose of knowledge discovery as the basic resource of adequate business decision making process representing a good base for analysis and predictions in the following time period for the purpose of quality business decision-making by top management.

(a) Show the steps in designing and development of data warehouse of the mentioned business system.

(b) Show the implementation of data mining algorithms for the purpose of  deducting rules, patterns and knowledge as a resource for support in the process of decision making.

Answer: Warehousing data is based on the premise that the quality of a manager's decisions is based, at least in part,on the quality of his information. The goal of storing data in a centralized system is thus to have the means to provide them with the right building blocks for sound information and knowledge. Data warehouses contain information ranging from measurements of performance to competitive intelligence.

Data mining tools and techniques can be used to search stored data for patterns that might lead to new insights. Furthermore, the data warehouse is usually the driver of data-driven decision support systems (DSS), discussed in the following subsection.

Thierauf (1999) describes the process of warehousing data

(a) Show the steps in designing and development of data warehouse of the mentioned business system.

The strategy for developing a data warehouse can be broken down into four steps:

1. Educate yourself. I recommend getting Business Intelligence Roadmap by Moss, Atre and Youdon, and reading it cover to cover before you start.

2. Determine business requirements. Not all data warehouses are the same. You need to understand why the requestor needs a data warehouse. What are they trying to accomplish – saving time in collecting data, higher quality of data,

(b) Show the implementation of data mining algorithms for the purpose of deducting rules, patterns and knowledge as a resource for support in the process of decision making.

Data warehousing is a technological trend for supporting the corporate decision process. This technology collects integrated and subject-oriented databases for decision support accesses. Online analytical processing (OLAP) is another information technology for decision support process. OLAP enables managers and analysts to interactively inspect large amounts of detailed and consolidated data from different aspects. OLAP can analyze complex relationships among large amounts of data items stored in multidimensional databases. However, the existing relationships, patterns, and trends among large databases are usually invisible or unknown.

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