The systematic accumulation of large amounts of data from


As we noted in the introduction, data warehousing -- the systematic accumulation of large amounts of data from multiple sources -- and data mining -- techniques for extracting meaning from those data -- have become the hallmarks of virtually all large organizations and many smaller ones. As the costs of acquiring data continued to plummet and the cost of storing it almost approaches zero, network organizational databases have become increasingly important to basic decision-making. While the jury is still out on whether decisions made on the basis of processing large amounts of data are substantially better than those made on other grounds, such as professional judgment and/or experience, there is no doubt that this trend will continue and probably accelerate at least through the next decade. Therefore, it becomes extremely necessary for prospective information technology managers to understand how such databases are constructed and how they can be used for decision purposes.

The first step in this case is to become moderately familiar with the terminology of databases and data processing. Here are two good sources to give you this background; if you are still uncertain about things or want to look into certain aspects in more detail, the optional readings provide additional material for you to consult:

VCILT Web TV (20111) Introduction to Data Warehousing and Data Mining. Youtube video. Retrieved December 20, 2011, from https://www.youtube.com/watch?v=dGDuD10U4-M

Gunther, O. (2011) Database Management Systems. Slideshare Presentation. Retrieved December 20, 2011, from https://www.slideshare.net/Databaseguys/o-gnther-database-management-systems

When you feel somewhat comfortable with this language, please review the following paper describing an exercise in data warehousing and data mining conducted by a Nigerian university using data drawn from its own student records and learning management system. Hopefully, this will resonate with your own experience, since Trident University is hoping to implement its own learning management system soon and use it not only to manage coursework but to collect useful data for planning purposes. Please pay particular attention to the kinds of data being assembled and the kinds of questions being asked of the data:

Akintola K.G., Adetunmbi A.O., and Adeola O.S. (2011) Building Data Warehousing And Data Mining From Course Management Systems: A Case Study of Federal University of Technology (FUTA) Course Management Information Systems. Information Technology for People-Centred Development (ITePED 2011). Retrieved December 20, 2011, from https://www.ncs.org.ng/wp-content/uploads/2011/08/ITePED2011-Paper4.pdf

When you've had a chance to read this article, review information from the background readings and research other sources on your own, please prepare a short paper on the topic:

Important information that A University might be able to obtain by warehousing and mining student records and learning management system data

Your paper should be between three and five pages. Take a definite stand on the issues, and develop your supporting argument carefully. Using material from the background information and any other sources you can find to support specific points in your argument is highly recommended; try to avoid making assertions for which you can find no support other than your own opinion.

  • relate the questions you identify to specific kinds of data

•indicate why you believe that the questions you identify are important to the University, and the kinds of decisions that you expect to be affected
•identify any problems you see in assembling and/or analyzing the data

 

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