Master | Analytics Business Intelligence

Durante questo Master verranno affrontate le tecniche di analisi dei dati, specialmente quelle basate sul data mining, che consentono l'estrazione automatica di conoscenza da grandi quantità di dati in modo interativo e adattativo permettendo di costruire progressivamente modelli astratti che consentano di rappresentare correlazioni e dipendenze di varia natura presenti nei dati.

Il master si compone di tre aree:

1- Basic

• Strategy and Marketing

• Accounting and Finance

• Management

• Supply Chain

• HR

• IS Architecture (structure of an Enterprise IS, building blocks, business processes and the IS, the ERP, information flows, concepts of business continuity)

• Mobile Technologies

• DBMS – DWH (Methods, architectures and tools of the traditional structured data processing approaches)

• Enabling Infrastructure (the baseline of an IS: hardware, virtualization, networking, storage, datacenters

2- More Than Tecnology: businees & personal skills

• BI & Analytics: what is it, why now the VUCA world (volatile, uncertain, complex, ambiguous); Analytics as a Strategy

• Analytics: the Big Picture, Data Visualization as a key enabler; Case Study on the impact and role of visualization

• More than Technology: Personal Skills required to be effective: Meeting Management; Active Listening; Situational Leadership Styles; the Power of Dialogue; Contextual Intelligence

• Creating Strong Strategies – required for effective Analytics and beyond: Â What is a Strategy; what are the Pressures on Making Strong Strategies; why Strategies matter now more than ever

• Analytics 3.0: How Big Companies use Big Data; Data Types, the Data Environment;

• Business Models: the key "differentiator"; Business Models framework, types, and building blocks; Case Studies

• Managing with Analytics

3- Core: Technology

• Data management & Pattern Recognition

• Exploratory Data Analysis & Data Mining

• Visualization

• Design Paradigm

• Development Strategies (mobile users)

• Online Analytical Processing

• Reporting, Cockpit, Corporate Performance Mng

• Big Data Technologies (operations)

• Architectural components of a big data infrastructure

• Hardware infrastructure, sizing and scaling

• The Hadoop stack and design principles

• Implementing and managing a big data system

• Other data processing technologies

• Semantic Web Technologies

• Natural language processing

• Indexing and index search

   

•  Atenei singoli o consorziati;
• Consorzi universitari, aventi titolo per il rilascio di Master Universitario di I o II livello;
• ATS tra Ateneo/i e impresa/e. Capofila del progetto sarà l'Ateneo e il Consorzio universitario.