AIMS AND CONTENT

LEARNING OUTCOMES

The first part of the course will focus on architectural aspects of transactional systems, query processing, transaction management and recovery. The second part will deal with the issues of data warehouse design, data mining and knowledge discovery techniques .The student will be able to apply the acquired skills in : Query processing Transaction management and recovery. Conceptual data warehouse project Fact and Snowflake models Logical data warehouse project Architecture of a Data Mart. Data mining and knowledge discovery techniques Frequent Pattern Analisys Classification techniques Decision tree and Bayesian Classifiers

SYLLABUS/CONTENT

The course will focus on architectural aspects of transactional systems, query processing, transaction management and recovery.
The second part of the course will address the issues of data warehouse project is the conceptual point of view and from the point of view of logic, will present the models Fact and Snowflake and architecture of a Data Mart.
In the third part the course will analyze and discuss techniques of data mining and knowledge discovery for the retrieval of information in large amounts of data, with particular reference to the Frequent Pattern Analysis and techniques of classification and prediction.

RECOMMENDED READING/BIBLIOGRAPHY

Kimball and Ross "The data warehouse toolkit" - Wiley & Sons 
Jiawei Han, Micheline Kamber, “Data Mining: Concepts and Techniques” - Morgan Kaufmann

TEACHERS AND EXAM BOARD

Exam Board

ANTONIO BOCCALATTE (President)

ALESSIO MERLO

MASSIMO PAOLUCCI

ALESSANDRO ARMANDO (President Substitute)

LESSONS

LESSONS START

https://courses.unige.it/11160/p/students-timetable

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Individual project and discussion

ASSESSMENT METHODS

Design capabilities compared to the training objectives

Exam schedule