DATA WAREHOUSING

DATA WAREHOUSING

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iten
Code
90508
ACADEMIC YEAR
2017/2018
CREDITS
12 credits during the 1st year of 9014 Computer Science (LM-18) GENOVA
SCIENTIFIC DISCIPLINARY SECTOR
INF/01
LANGUAGE
English
TEACHING LOCATION
GENOVA (Computer Science)
semester
Annual
Teaching materials

AIMS AND CONTENT

LEARNING OUTCOMES

Students will be provided with a sound grounding on theoretical, methodological, and technological fundamentals concerning the management and analysis of data in decision support systems, with a specific reference to data warehousing architectural and design issues. Students will learn key elements of data integration and governance, data quality and cleaning, Extraction-Transformation-Loading processes, conceptual, logical, and physical design of data warehouses, storage architectures and scalable parallel processing, use of data warehouses for business reporting and online analytical processing. Students will also learn key elements on conceptual and notational tools for business modelling. Students will be involved in project activities.

Teaching methods

Class, project and outside preparation

SYLLABUS/CONTENT

The course will introduce the main architectural and design issues related to data management and analisys in decision support systems (data warehousing), comparing them with classical transactional data management systems.
Introduction Computer aided decision support systems. OLAP vs OLTP. Data warehousing , data mining, business intelligence.  Data warehousing system architecture.

Data exploration, integration, and cleaning. Data wrangling and ETL processes. Data governance, data quality, and data cleaning.

Data models for data warehousing. Multidimensional data model. Dimensions,measures, and hierarchies.

Back-end.  Storage alternatives and massively parallel query processing.  Storage structures and indexing. Materialized views. Query optimization.

Data warehouse design. Conceptual, logical, and physicial design.

Front-end.  OLAP queries and reporting. OLAP SQL extensions.

Business process modelling:

  • Visual notations for business process modelling
  • Use of the models for the analysis, re-engineering and design of business processes, taking into account the data related aspects (collection, storage and analysis)

TEACHERS AND EXAM BOARD

Ricevimento: Appointment by email Office: Valle Puggia – 301

Ricevimento: Appointment by email Office: Valle Puggia – 328

Ricevimento: Appointment by email

Exam Board

GIOVANNA GUERRINI (President)

ELENA ZUCCA

GIANNA REGGIO

BARBARA CATANIA

LAURA DI ROCCO

LESSONS

Teaching methods

Class, project and outside preparation

EXAMS

Exam description

Written examination, oral examination and project discussion