Topics in Technology Mgt
Topics in Technology Mgt MGT 296
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This 4 page Class Notes was uploaded by Ludwig Satterfield on Wednesday September 9, 2015. The Class Notes belongs to MGT 296 at University of California - Davis taught by Yinghui Yang in Fall. Since its upload, it has received 50 views. For similar materials see /class/191952/mgt-296-university-of-california-davis in Business, management at University of California - Davis.
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Date Created: 09/09/15
MGTP 296 Business Intelligence Technologies Data Mining Spring 2008 University of California Davis Graduate School of Management Professor Yinghui Catherine Yang Room 145 AOB IV UC Davis 5307545967 yiyangucdavisedu httpfacu1tygsmucdaviseduyiyang Davis Mondays 1210 300 pm 261 AOB IV San Ramon Saturdays 9 1200n and 1 400pm on Apr 5 19 May 3 17 31 Course Description Data is a key source of intelligence and competitive advantage for business organizations With the explosion of electronic data available to organizations and the demand for better and faster decisions the role of data driven intelligence is becoming central in organizations Data mining is the process of converting the raw data into useful knowledge required to support decisionmaking It automates the process of knowledge discovery making us orders of magnitude more productive in our search for useful information than we would be otherwise It also increases the confidence with which we can make business decisions Virtually every business organization these days is in the process of exploring and implementing data mining solutions to core business problems This course is essential for anyone interested in understanding how to get the maximum value from data especially when abundant data are available Application areas covered in this course include marketing customer relationship management financial forecasting risk management personalization Web searching etc The course focuses on two subjects simultaneously The essential data mining and knowledge representation techniques used to extract intelligence from data and experts Such techniques include decision trees association rule discovery clustering classification neural networks nearest neighbor link analysis etc 2 Common problems from Marketing Finance and Operations that demonstrate the use of various techniques Tbs cams 1s smwmred 5a um n 15 senbbxe bmb fax students mtnested m a camepmal mdzxslmdmg afdmn mm and s pamnnal as wellas this mtexestzdm nndzxstnndmg u dam andquan handsanskdls lmzndzd A em Fully n21 Tbs cause 15 ncammzndzdfax sludan mtnestedm mdzxsundmg u ceebmques and applicath af am mmmg fax makmg mtelhgem busmzss dzclsmns m amends axgamnna se ts emexescea m Mumquot bx Fume mu 515a rm Lhs esmse useful Nb pnax kmwledge 1s xeqnued fax mm Lhs esmse MGTMGP 2m bx MGTMGP 227 are nmpzexeqwsmsanhs cams Tuxdnmk Tm Bunk Data Mjning D T W F hm w Mrkwwm 15 amber u Rainsth mum seem Em Meebsex aenyma Gardnn Lmn 2mm Wuey Isamn n47147n643 15mm 972en4m7n549 Cuunewd me dams ed teach 2965 85965 2 11th We wl mkz exebswe use bnbe Web m2 mthls amuse Impumm mfanmman fax be ebss e g annmmcemems 12mm mums and aththandnms wdlapparan be Web 5m Yanshmdd mkz bsbn afchzckmg n regularly Nsce Thls sylth maychmge during me qumx Tbs esmse Web 5 Va always have u mast upeseasee sylth O zeHnux Knack an my dam axbyappmmmem 0 cm me anyume yml have a quzstmn Grading Term Project Each group 2 or 3 students is responsible for choosing a company to study its data utilization situation and make recommendations about how its data should be used for generating business intelligence There are two phases In phase 1 which is due in the middle of the quarter each group needs to turn in a 23 page writeup about the company they picked and generally describe its data situation Phase 2 is due before the last class in which each group presents its project to the entire class In the nal project report each group needs to follow detailed guidelines to analyze the company s data strategies and make detailed recommendations based on the techniques and strategies we learned from the class If possible a group can also obtain some sample data from the company and make detailed analysis for the company More detailed guidelines for the project will be made available to you after class starts Out of the 30 points 25 points will be given to the project as a whole 5 points will be based on group peer evaluation Homework There are 4 homework assignments in total Each counts 15 of the total grades In each homework assignment you are given a dataset and will need to follow the guidelines to analyze the data and write a report You should work on them individually Policies I ll try my best to create a healthy learning environment both in the classroom and after class Nonclass related activities are discouraged in class Please try your best to be on time for the class After a class you are responsible for reviewing the materials covered and reading the related text before the next class Attendance Attendance is required for this course Class Schedule Subject to change Davis Day lecture scheduled on a different day San Ramon Note Business applications cases software demonstrations and short student presentations will be blended into each lecture