The course addresses Enterprise information systems with reference to models and architectures of business processes covering front-end systems (e.g., Customer Relationship Management systems- CRM), back-end systems (e.g., Enterprise Resource Planning systems -ERP), enterprise governance (e.g., Business Intelligence- BI). The course specifically focuses on methodological aspects related to analysis and design of datawarehouses. More recent requirements and challenges offered by big data will be discussed.
Expected learning outcomes
Lesson period: First semester
(In case of multiple editions, please check the period, as it may vary)
Enterprise information systems. Organizational model (operation systems, management systems, analysis systems). IT model (application model, technology model). Functional model (use case model, process model, data model).
Business processes. Definition of Business Process (BP) - the CRASO paradigm. A classification of BP. Business processes modeling.
ERP systems. ERP paradigm and reference architecture. CRM systems. CRM paradigm and reference architecture. CRM evolution.
Business Intelligence and decision support systems. Requirements and features of business information. Reference architetture and system layers. Datawarehouses. Basic concepts and definitions. Architecture for data warehousing. Data source layer. Transformation layer: analysis and reconcicliation of data sources. Storage layer: conceptual and logical design of the DW. Processing layer: reporting, OLAP, data mining. Relational DW: ROLAP schemas and queries.
Enterprise systems and Big Data. Big data e Linked Open data for decision support. Opinion mining and sentiment analysis for decision support. New requirements and challenges. The SMAC (Social, Mobile, Analytics and Cloud) paradigm.
- 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.