This Web page provides a brief introduction to data mining. It contains 23 links for examples or further explainations on data mining concepts. Two popular data mining techniques, regression analysis and classification, are discussed briefly. A link to in-depth coverage of Classification technique is provided.
The page is replete with links to enhanced information. Unfortunately many of them no longer work.
Type of Material:
Lecture. Tutorial.
Recommended Uses:
It can be used as a reading assignment for Management Information Systems courses.
Technical Requirements:
The site is essentially text including links. It requires only a basic Internet connection and browser. No specific hardware, operating system, browser, plug-ins or access speed is required.
Identify Major Learning Goals:
Introduce the topic of data mining and give an overview of the uses, process and goals.
Target Student Population:
Students of business information systems in general and database in particular. Also professionals. Undergraduate students.
Prerequisite Knowledge or Skills:
An understanding of databases would be beneficial.
People interested in the data mining techniques will benefit from an understanding of statistics.
Content Quality
Rating:
Strengths:
It explains data mining in general terms in the main text with links to more examples and detailed explanations. Two popular data mining techniques are explained in more detail. If students want to learn more, they can open the link (for example, Classification Trees)for in-depth coverage. External references are provided in each area.
Concerns:
The content in main text is only a shallow introduction. Many links are not working, which makes the article incomplete since some examples and concepts are illustrated through links.
Potential Effectiveness as a Teaching Tool
Rating:
Strengths:
The material is useful to introduce the concept of data mining. The presentation of information is clear; The authors use the need and haystack analogy to explain the process of finding the answer to a specific business question in a large amount of data.
Concerns:
Concrete examples, intended to be available through remote links, are often not available.
Privacy issues, a concern enhanced by the increasingly sophisticated use of data collection and analysis techniques, were not mentioned, but perhaps that's outside of the purpose of this brief introduction.
Ease of Use for Both Students and Faculty
Rating:
Strengths:
The main text is contained on one web page so it's easy to go through the material. Including in-depth coverage in links helps students read the articl more efficiently.
Concerns:
There are 23 links in the article. Among them, at least 7 links return error message "The page requested could not be found!".
Lynn Aaron
Creative Commons:
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