Information Systems
A.Y. 2025/2026
Learning objectives
Goal of the course is to introduce basic concepts on Enterprise information systems with reference to models and architectures of business processes covering front-end systems, back-end systems, enterprise governance. The course specifically focuses on methodological aspects related to datawarehouse analysis and design, with focus on data extraction and integration activities, by also presenting basic notions of big data analysis systems and their possible roles in enterprise activities.
Expected learning outcomes
Students will be able to effectively analyze information systems architectures, by critically discussing and motivating different architectural solutions. Students will be able to apply concepts and methods introduced in the course to solve simple datawarehousing analysis and design problems.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
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
First semester
Course syllabus
I - Enterprise Information Systems
Role, characteristics, and functions of enterprise information systems. Data organization and support for business processes. Enterprise information systems: ERP (Enterprise Resource Planning) systems, CRM (Customer Relationship Management) systems, SCM (Supply Chain Management) systems. The Information Systems function and professional roles. Information systems, ICT, and digital scenarios: design and development, cloud computing, main digital trends.
II - Business Intelligence
Decision-making processes and decision support. Managerial information needs: OLTP vs. OLAP. Architecture of a Business Intelligence system. Data warehouse and data mart. Architectures for data warehousing. ETL (Extraction, Transformation, and Load). Data integration. Conceptual and logical design of a datawarehouse. Datawarehouse population. Business reporting, OLAP, data mining.
III - Big Data Analytics, AI-based and Cloud-based Analytics
Big data and data lakes. Big data analytics. Text, Web, and Social Media Analytics. Sentiment analysis and main applications. Main solutions for AI-based and cloud-based analytics.
Role, characteristics, and functions of enterprise information systems. Data organization and support for business processes. Enterprise information systems: ERP (Enterprise Resource Planning) systems, CRM (Customer Relationship Management) systems, SCM (Supply Chain Management) systems. The Information Systems function and professional roles. Information systems, ICT, and digital scenarios: design and development, cloud computing, main digital trends.
II - Business Intelligence
Decision-making processes and decision support. Managerial information needs: OLTP vs. OLAP. Architecture of a Business Intelligence system. Data warehouse and data mart. Architectures for data warehousing. ETL (Extraction, Transformation, and Load). Data integration. Conceptual and logical design of a datawarehouse. Datawarehouse population. Business reporting, OLAP, data mining.
III - Big Data Analytics, AI-based and Cloud-based Analytics
Big data and data lakes. Big data analytics. Text, Web, and Social Media Analytics. Sentiment analysis and main applications. Main solutions for AI-based and cloud-based analytics.
Prerequisites for admission
Fundamental notions of relational databases and RDBMS are required (database design, data modeling, schema definition and query languages).
Teaching methods
The teaching consists of lectures, supported by the use of slides. For more technical/design topics, exercises are also performed, which are commented on in the classroom. Slides, which follow the lectures' and exercises contents, are available on the MyAriel website of the course. Furthermore, seminars are given on advanced projects to involve students in concrete applications of information system concepts and architectures presented during the course.
Teaching Resources
Textbooks suggested:
- G. Bracchi, C. Francalanci, G. Motta. Sistemi Informativi d'impresa. McGraw-Hill - 2010 (Chapters 1,2,3,4,5,9)
- M. Golfarelli, S. Rizzi. Data Warehouse - Teoria e pratica della progettazione (2 ed.). Mc-Graw Hill, 2006 (Chapters 1,2,3,4,5 (until 5.2.10 included), 6 (until 6.1.8 included), 8, 9 (until 9.1.10 included)).
Lecture slides will be published on the MyAriel course website https://myariel.unimi.it/course/view.php?id=8363.
- G. Bracchi, C. Francalanci, G. Motta. Sistemi Informativi d'impresa. McGraw-Hill - 2010 (Chapters 1,2,3,4,5,9)
- M. Golfarelli, S. Rizzi. Data Warehouse - Teoria e pratica della progettazione (2 ed.). Mc-Graw Hill, 2006 (Chapters 1,2,3,4,5 (until 5.2.10 included), 6 (until 6.1.8 included), 8, 9 (until 9.1.10 included)).
Lecture slides will be published on the MyAriel course website https://myariel.unimi.it/course/view.php?id=8363.
Assessment methods and Criteria
The exam is written with a duration of 75 minutes, it covers all the topics of the program and it consists of questions and exercises. The final evaluation, expressed in thirtieths, takes into account the level of knowledge and mastery of the topics, considering clarity of exposition and accuracy of language, as well as the ability to solve design-type exercises.
Professor(s)