Business Information Sistems

A.Y. 2021/2022
6
Max ECTS
48
Overall hours
SSD
INF/01
Language
English
Learning objectives
The aim of this course is to let the student appreciate the way that Information Systems (IS) can aid the realization of business objectives. In particular this course is aimed at providing:
· a critical understanding of role of IS in enabling business transformation;
· a critical understanding of some of the key issues in IS management;
· an understanding of why IS systems fail and approaches to counter these problems;
· a knowledge of several case studies in IS development and use.
Expected learning outcomes
· a critical understanding of role of IS in enabling business transformation;
· a critical understanding of some of the key issues in IS management;
· an understanding of why IS systems fail and approaches to counter these problems;
· a knowledge of several case studies in IS development and use.
Single course

This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.

Course syllabus and organization

Single session

Responsible
Lesson period
Second semester
If it is not possible to carry out ordinary face-to-face lessons, following the schedule provided for teaching, the lessons will be held through the Teams platform in synchronous mode.

On the course page on Ariel, students will be able to find all the information on the lectures and any changes to the programme and its related documents (bibliography etc) in case of lockdown.
The means and criteria for participation in the live lectures, which will need booking through a specific app, will be indicated on the University website.
Finally, in case it proves impossible to hold the exam face to face, the exam will take place remotely, in ways which will be communicated on the course page on Ariel at the end of the course.
Course syllabus
The program is organized in the following subtopics

· + Introduction
-- Information Systems in Organizations
-- Development Lifecycle
-- Knowledge Uplift Model
+ Performance Analytics
-- Performance Measures
-- Time Series Analysis
-- Frequent Pattern Mining
-- Process Mining
-- Event Logs
-- Data Preparation
-- Variant Analysis
-- Process Discovery
-- Conformance Checking
-- Comparative Process Mining
+ Conclusions
-- Knowledge Uplift in Process Mining
-- Advanced Process Mining Techniques
Prerequisites for admission
Basic notions of Python are propaedeutic to the activities proposed in class.
Teaching methods
The topics of the course will be addressed through lectures, with the help of transparencies and teaching materials that the teacher will make available from time to time on the Ariel platform. During the lessons exercises and demonstrations will also be carried out to help the student's learning path. A lesson will be dedicated to exam simulation.
Attendance, although not mandatory, is strongly recommended.
Teaching Resources
Slides and exercises proposed in class.

The following textbooks are suggested:

Business Information Systems
by Mukerjee, Prithwis
https://businfosystems.wordpress.com/presentations/

Fundamentals of business intelligence
by Grossmann, Wilfried; Rinderle-Ma, Stefanie
Springer 2015
http://unimi.summon.serialssolutions.com/#!/document?id=FETCH-unimi_catalog_USM19143012

Process mining: discovery, conformance, and enhancement of business processes
by Aalst , Wil M. P. : van der
Springer 2011
http://unimi.summon.serialssolutions.com/#!/document?id=FETCH-unimi_catalog_USM18357592
Assessment methods and Criteria
The verification test consists of a compulsory oral exam.
During the exam the student have to present a project in which some of the methodologies and tools presented in class will be applied to a case study identified with the teacher.

The examination procedures for students with disabilities and / or with DSA must be agreed with the teacher and the competent Office. International or Erasmus incoming students are invited to contact the course teacher in a timely manner.
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
Professor: Ceravolo Paolo
Professor(s)
Reception:
Thursday 14.00 - 15.00
Computer Science Department- 7° floor