Analisi delle prestazioni aziendali

This course presents techniques for Business Analytics according to two views: The process-driven view of Business Process Modeling and the data-driven view of Business Intelligence. The two views are dealt with in the two modules of the course. The first presents the main concepts and problematic issues related to the process management, where processes are  understood as workflow over some basic activities, and shows some of the languages, conceptual models and tools that can help to handle the main problems in a proper way. During the course, the students will become acquainted with the technical terminology of the area, with several rigorous models that can be used to structure and compose processes, with the logical properties that such processes can be required to satisfy and with specific analysis and verification techniques. Moreover, they will be given the possibility to experiment with some advanced tools for the design and analysis of business processes.The second module presents technologies and systems for data access, for building and analysing data warehouses, for reporting, and for knowledge discovery in databases. The accent of the module is on the use of tools and on the analysis of application problems by means of non-trivial samples and case studies. The student will be aware and able to manage the main technologies of Business Intelligence, specifically software products for effective decision support. The student will be able to independently evaluate methodologies, technologies and tools best suited for the analytical problem at hand. 

Theoretical notions required by the module are taught in the courses of the first semester 426AA “Basi di dati di supporto alle decisioni”, 420AA “Data mining I”, and in the course of the second semester “Data Mining II”.

The module presents technologies and systems for data access, for building and analysing datawarehouses, for reporting, and for knowledge discovery from data. The focus is on tools, systems and problem solving methodologies, with case studies and applicative problems. The course also provides useful means for the typical work performed during the final thesis.

The student will have knowledge about the main software technologies for accessing data; for designing and developing datawarehouses, OLAP data cubes, and reports; and for extracting and applying predictive data mining models.

The student will be able to use software tools for the design of datawarehouses, for their population through ETL flows, for the design and the query of OLAP data cubes, for the design of reports and dashboards in support of business decisions.  The student will be also able to apply data mining tools to extract models from data, with special reference to predictive models for marketing and CRM.

The student will be able to assess, with indepence and autonomy, the current and future software technologies for Business Intelligence with regard to the requirements of a specific data analysis task.

Introduction
Introduction, objectives. The architecture of Business Intelligence.

Data access
File data access. Formats: CSV, FLV, ARFF, XML, binary and compressed. API Java. Standards for RDBMS data access: ODBC, JDBC, OLE DB, ADO. Details on API JDBC. Tools: Java, SQL Server 2012. Lab practice. 

The Extract Transform and Load (ETL) process 
Data access, selection, cleaning and transformation tasks. Populating a datawarehouse: surrogate keys and slowly changing dimensions. Tools: Java, SQL Server 2012 Integration Services. Lab practice. 

Data warehousing, OLAP and reporting
Querying a datawarehouse with analytic SQL. Building OLAP data cubes. Querying OLAP data cubes with MDX. Reporting with Excel pivot tables. Designing reports and dashboards. Tools: SQL Server 2012 Analysis Services, Microsoft Excel, SQL Server 2012 Reporting Services. Lab practice. 

Knowledge discovery
The knowledge discovery process. Data mining models: classification, association rules, clustering. Tools: Weka Explorer and Knowledge Flow. Lab practice. 

Articles, book chapters, and manuals will be provided at the course web site. Software tools will be downloadable with an academic licence.

Il corso si pone l'obiettivo di illustrare i concetti principali e le problematiche inerenti la gestione dei flussi di lavoro nei processi aziendali e di fornire una ampia panoramica dei modelli concettuali, dei linguaggi e degli strumenti di progettazione e analisi basati su essi.

Lo studente acquisira' familiarita' con le notazioni piu' diffuse per la rappresentazione dei processi (EPC, BPMN, BPEL, ...) e sapra' formalizzare i principali requisiti di correttezza dei processi in termini di proprieta' di modelli basati su reti di Petri. Inoltre, lo studente apprendera' i concetti elementari del process mining per la scoperta di processi a partire dai log di esecuzione di un sistema, per valutare la conformita' tra processi e log e per confrontare processi.

Lo studente sapra' utilizzare strumenti di modellazione dei processi e tecniche di trasformazione da notazioni grafiche a reti di Petri. Lo studente sapra' utilizzare strumenti di verifica semi-automatica (WOPED, WOFLAN,...) per l'analisi dei processi.

Lo studente sapra' valutare l'adeguatezza dei linguaggi e degli strumenti di progettazione, analisi e verifica rispetto alle caratteristiche richieste dal contesto aziendale.

Il corso si propone di conciliare le tecniche di astrazione proprie delle notazioni grafiche, con l'approccio strutturato e modulare e coi modelli operazionali propri della ricerca scientifica in ambito informatico, mostrando l'impatto dalle proprieta' di interesse ai fini della analisi e della verifica automatica sulla scelta dei linguaggi e modelli da utilizzare per la specifica e la progettazione di processi. Il percorso di apprendimento portera' gli studenti ad acquisire dimestichezza con i termini tecnici dell'area, con i diversi modelli per strutturare e comporre i processi in modo rigoroso, con le proprieta' logiche che questi modelli possono essere richiesti soddisfare e con le tecniche di analisi e verifica dei processi. Inoltre potranno sperimentare i concetti visti con strumenti automatici per progettare e analizzare processi.

The course aims to reconcile abstraction techniques and high-level diagrammatic notations together with modular and structural approaches. The objective is to show the impact of the analysis and verification properties of business processes on the choice of the best suited specification and modelling languages. At the end of the course, the students will gain some familiarity with business process terminology, with different models and languages for the representation of business processes, with different kinds of logical properties that such models can satisfy and with different analysis and verification techniques. The students will also experiment with some tools for the design and analysis of business processes.

Introduzione al corso. Business process management. Evoluzione delle architetture di riferimento. Modelli concettuali e meccanismi di astrazione. Reti di Petri: invarianti, S-systems, T-systems, reti free-choice e loro proprieta'. Reti di workflow e moduli. Workflow patterns. Event-driven Process Chains (EPC). Business Process Modelling Notation (BPMN). Yet Another Workflow Language (YAWL). Business Process Execution Language (BPEL). Process Mining.

Weske: Business Process Management: Concepts, Languages, Architectures ISBN 978-3-642-28615-5. Springer-Verlag Berlin Heidelberg 2012. (main reference)

Verbeek, Basten, van der Aalst: Diagnosing workflow processes using Woflan. (article, recommended reading)

van der Aalst, van Hee: Workflow Management: Models, Methods, and Systems (book, optional reading)

Desel, Esparza: Free Choice Nets (book, optional reading)