Scheda programma d'esame
DECISION SUPPORT DATABASES
SALVATORE RUGGIERI
Anno accademico2017/18
CdSDATA SCIENCE AND BUSINESS INFORMATICS
Codice662AA
CFU6
PeriodoPrimo semestre
LinguaItaliano

ModuliSettoreTipoOreDocente/i
DECISION SUPPORT DATABASESINF/01LEZIONI48
SALVATORE RUGGIERI unimap
Programma non disponibile nella lingua selezionata
Learning outcomes
Knowledge

The student who completes the course successfully will be able to demonstrate advanced knowledge of the main issues related to the use of specific databases, the Data Warehouse, organized to create the right models for measurable key business processes, to support informed decisions about how to improve them. The student will acquire knowledge of the fundamental concepts about a conceptual model for designing data warehouses used to analyze key business processes that are measurable and worthy of improvements, the logical data model to implement them, the analytic SQL for producing interesting reports to evaluate the performance of the modeled key processes in order to improve them. Lastly, the student will be aware of how to use a specialized DBMS in the right way to develop a best performing business intelligence application.

Assessment criteria of knowledge

The assessment of the course consists of a written and an oral exam. In the written exam, the student must demonstrate the use of knowledge of the course contents to solve problems. During the oral exam the student must be able to demonstrate knowledge of the course contents and be able to discuss the topics thoughtfully and with propriety of expression.

 

Skills

The student will be able to design Data Warehouses, to query them using analytic SQL queries, and to optimize them using indexes and materialized views.

Assessment criteria of skills

The written exam will include design exercises, SQL query writing, and optimization analysis exercises.

Behaviors

The student will be able to critically approach complex design processes which require interpreting user requirements.

Assessment criteria of behaviors

The written exam will include design exercises with user requirements in natural language form.

Prerequisites

A Bachelor level course in Databases, including the following topics: relational algebra, SQL, DBMS architetctures.

Prerequisites for further study

This course provides the necessary background for the courses "Laboratory of Business Intellligence" (module 2 of 417AA) and "Laboratory of Data Science" (664AA).

Teaching methods

Teaching methods: face to face lectures

Learning activities:

  • attending lectures
  • participation in discussions
  • individual study
  • exercises
  • office hours

Attendance: strongly advised

Syllabus

The course presents the main approaches to the design and implementation of decision support databases, and the characteristics of business intelligence tools and computer based information systems used to produce summary information to facilitate appropriate decision-making processes and make them more quick and objectives. Particular attention will be paid to themes such as conceptual and logical Data Warehouses design, data analysis using analytic SQL, algorithms for selecting materialized views, data warehouse systems technology (indexes, star query optimization, physical design, query rewrite methods to use materialized views). A part of the course will be dedicated to a collection of case studies.

Bibliography

Decision Support Databases Essentials, A. Albano and S. Ruggieri, 2016. The textbook is available for free on the web.

Databases Essentials, A. Albano, 2016. The textbook is available for free on the web.

Non-attending students info

There is no specific rule for non-attending students.

Assessment methods

The exam consists of a written part and an oral part. The written part consists of open questions, small exercises, and a Data Warehous design problem. Examples with solutions are provided at the course home page. Students are admitted to the oral part if they receive a grade of at least 18/30. Oral consists of open questions on the topics of the course. 

Ultimo aggiornamento 17/07/2017 17:17