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BUSINESS INTELLIGENCE

CODE 60270
ACADEMIC YEAR 2021/2022
CREDITS 6 credits during the 2nd year of 8734 Management Engineering (LM-31) GENOVA
SCIENTIFIC DISCIPLINARY SECTOR ING-INF/05
LANGUAGE Italian (English on demand)
TEACHING LOCATION GENOVA (Management Engineering)
SEMESTER 1° Semester
TEACHING MATERIALS AULAWEB

OVERVIEW

The course introduces the basic concepts of Business Intelligence (BI) with particular reference to aspects of Analytics/Data Mining and focusing on the use analytical methods and reporting to support business decisions.

AIMS AND CONTENT

LEARNING OUTCOMES

The course introduces the basic concepts of Business Intelligence (BI) with particular reference to aspects of Analytics/Data Mining and focusing on the use analytical methods and reporting to support business decisions. The students will acquire both the basic skills for the design of a BI system and the ability to critically evaluate the data analysis performed with Data Mining tools. During the course some seminars are planned that illustrate real cases of application of the BI in the enterprise.

TEACHING METHODS

Lectures and computer assisted lab sessions.

SYLLABUS/CONTENT

Introduction to Business Intelligence (BI): problems methods and tools.

Components of a BI system: ETL, Data Mart and Data Warehouses, On Line Analytical Processing (OLAP), Reports and Dashboards, Analytics and Data Mining.

Analysis and definition of Key Performance Indicators (KPIs).

Analytics: Basic concepts of statistical inference, Exploratory Data Analysis (EDA).

Tools and Techniques of Data Mining: decision trees and association rules, Naive Bayes, linear methods for classification and regression, Artificial Neural Networks, Support Vector Machine and kernel methods; Clustering methods; Quality Assessment of Data Mining techniques .

Business case studies.

RECOMMENDED READING/BIBLIOGRAPHY

Lecture notes provided during the course.

Further readings:

•          C.Vercellis, Business Intelligence: modelli matematici e sistemi per le decisioni, McGraw-Hill, 2006.

•          P.Giudici, Data Mining: metodi informatici, statistici e applicazioni, McGraw-Hill, 2003.

•          J.Han, M.Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann, 2006 (2nd Ed.).

TEACHERS AND EXAM BOARD

Exam Board

DAVIDE ANGUITA (President)

LUCA ONETO

ARMANDO TACCHELLA

LESSONS

Class schedule

All class schedules are posted on the EasyAcademy portal.

EXAMS

EXAM DESCRIPTION

Oral examination. The student will develop autonomously (individually or in cooperation with other students) a case study, selected among those proposed as exam topics and using the methods discussed during the course. The oral examination will focus on the discussion of the case study.

Exam schedule

Date Time Location Type Notes
20/12/2021 09:30 GENOVA Orale
20/12/2021 14:30 SAVONA Orale
11/01/2022 09:30 GENOVA Orale
26/01/2022 09:30 GENOVA Orale
14/02/2022 09:30 GENOVA Orale
09/06/2022 09:30 GENOVA Orale
06/07/2022 09:30 GENOVA Orale
14/09/2022 09:30 GENOVA Orale