Scheda programma d'esame
LABORATORIO DI BUSINESS INTELLIGENCE
(BUSINESS INTELLIGENCE LABORATORY)
ANNA MONREALE
Anno accademico2017/18
CdSINFORMATICA
Codice353AA
CFU6
PeriodoPrimo semestre
LinguaInglese

ModuliSettore/iTipoOreDocente/i
LABORATORIO DI BUSINESS INTELLIGENCEINF/01LABORATORI48
ANNA MONREALE unimap
Obiettivi di apprendimento
Learning outcomes
Knowledge

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

Assessment criteria of knowledge

The student will be assessed on his/her demonstrated ability to use tools and methodologies of the Business Intelligence for problem solving. There is a lab exam (4 hours) and an oral exam.

Methods:

  • Final oral exam
  • Final laboratory practical demonstration
Skills

The student will be able to use software languages and 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 decision making.  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.

 

Assessment criteria of skills

Skills will be assessed through a project for the first module and lab exam for the second module. 

Behaviors

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.

Modalità di verifica dei comportamenti

Autonomy and indepence in tool evaluation will be assessed during the lab practices and at the oral exam.

Prerequisites

The theoretical notions required by the module are taught in the courses of the first year 600AA “Decision Support Databases” and 420AA “Data mining”.

Teaching methods

Delivery: face to face

Learning activities:

  • attending lectures
  • individual study
  • group work
  • Laboratory work

Attendance: Advised

Teaching methods:

  • Lectures
  • Task-based learning/problem-based learning/inquiry-based learning
  • laboratory

The course will be held in a lab room. After briefly introducing topics and software tools, students will exercise in problem solving. Solutions will be discussed all-together.

Syllabus

The module presents Business Intelligence technologies and systems for data access (file formats, RDBMS standards), for building and analysing datawarehouses (ETL, OLAP), for reporting, and for knowledge discovery from data. The focus is on tools, systems and problem solving methodologies, with case studies and application problems.

Bibliography

Book chapters with reminds on theoretical background and software manuals will be provided at the course web site. Software tools will be downloadable with an academic licence.

Non-attending students info

No specific rules for non-attending students.

Assessment methods

Lab practice and oral.

Ultimo aggiornamento 19/07/2017 18:27