Supporting Material for CN3023: Databases 3

• Module Code: CN-3023
• Dept. module Code: CT314
• Module leader: Dr Goran Nenadic
• School resposnible: Informatics
• Credit rating: 15
• Pre-requisite: CN-1005 (Databases 1)

Aims

The aim of this module is to provide students with broad knowledge of emerging database technologies. Students will learn about object-oriented, mobile, textual, XML and multimedia databases, and data warehousing and data mining techniques, and their role in data and information management.

Learning outcomes

On successful completion of this module, students should be able to

• Academic knowledge
  Have a broad understanding of emerging database technologies and their applications.
• Intellectual skills
  Understand key issues, advantages and problems of emerging database technologies.
  Compare and contrast various database paradigms
  
• Subject practical skills
  Gain some knowledge of practical applications in emerging database technologies.
  
• Transferable skills
  Apply advanced database techniques to a broad range of applications.
  

Syllabus

• Emerging database technologies and applications (overview)
• Object-oriented databases
• Data warehousing
• Data mining techniques
• XML, textual, multimedia and Web databases
• Mobile databases and networks (overview)

Reading list

• (textbook) R. Elmasri & S.B. Navathe, Fundamentals of Database Systems, 4th edition, Addison Wesley, 2004 (ISBN 0-321-20448-4)
• (textbook) T.M. Connolly, C.E. Begg, Database systems: a practical approach to design, implementation, and management, 4th edition, Addison-Wesley, 2005 (ISBN 0-321-21025-5)
• C.J. Date, An Introduction to Database Systems, 8th ed, Addison Wesley, 2004 (ISBN 0-321-19784-4)
• L. Dunckley, Multimedia Databases: An Object Relational Approach, Addison-Wesley, 2003 (ISBN 0-201-78899-3)
• M. Graves, Designing XML Databases, Prentice Hall, 2001, (ISBN 0-13-088901-6)
• A. Silberschatz, H. Korth, S. Sudarshan, Database System Concepts, 5th edition, McGraw-Hill, 2005 (ISBN 0-07-295886-3)

Assessment

Assessment consists of 100% examination. The exam consists of one compulsory question (containing short questions) and two long questions (selected from three). Calculators are allowed.

Past examination papers

Revision questions:

• Part I
• Part II
• Part III
• Part IV

Lecture notes

• Lecture 1: "Overview of Database Technologies and Architectures"
  
  
• Lecture 2: "Introduction to Object-oriented Databases"
  • The Object Oriented Database System Manifesto
  • Object Data Management Group: http://www.odmg.org
  • Object Database Management Systems, the Resouce Portal for Education and Research: http://www.odbms.org
    
    
• Lecture 3: "Data Warehousing"
  • A case study (EDEKA)
  • A case study (Barnes and Noble, Inc.)
  • Oracle9i Warehouse Builder demo
  • Chaudhuri, Dayal: An overview of data warehousing and OLAP technology
• Lecture 4: "OLAP"
  • OLAP report
  • Microsoft Business Intelligence
  • SQL Server 2000 Resource Kit, Part 5: Data Warehousing
  • SQL for Aggregation in Data Warehouses
  • OLAP demo from BusinessObjects
    
    
• Lecture 5a: "Introduction to Data Mining [Part I: Introduction]"
  • U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth: From Data Mining to Knowledge Discovery in Databases, AI Magazine 17(3): Fall 1996, pp. 37-54
• Lecture 5b: "Association Rules"
  • Apriori - Association Rule Induction / Frequent Item Set Mining software
• Lecture 6: "Introduction to Classification"
  • Decision tree tutorial
  • Dtree - Decision and Regression Tree Induction software
  • svmlight: http://www.cs.cornell.edu/People/tj/svm_light/
  • SVMLIB: http://www.csie.ntu.edu.tw/~cjlin/libsvm
  • Precision and recall
• Lecture 7: "Introduction to Clustering"
  • K-means tutorial
  • Hierarchical clustering example
• Lecture 8: "Introduction to Information Extraction and Text Mining"
  • http://www.text-mining.org/
  • http://www.scils.rutgers.edu/~msharp/text_mining.htm
  • Marti A. Hearst: Untangling Text Data Mining
• Lecture 9: "Introduction to Multimedia Databases"
  • Building the Semantic Web
  • RIAO conferences on Large-Scale Semantic Access to Content (Text, Image, Video and Sound)
    (see RIAO proceedings 2004)
• Lecture 10: "Introduction to XML Databases"
  • On-line XML validation
  • XQuery/X-Hive demo
  • XML Database Products: Native XML Databases
• Lecture 11: Revision
  • Mock exam paper
  • Part I
  • Part II
  • Part III
  • Part IV

Other resources

• Object Data Management Group: http://www.odmg.org
• Object Database Management Systems, the Resouce Portal for Education and Research: http://www.odbms.org
  
  
• Weka 3: data mining software
• Weka tutorial
  
  
• UK National centre for Text Mining (NaCTeM)
• www.textmining.net
  
  
• www.w3.org/
• www.w3schools.com/