Information management
A.A. 2018/2019
Obiettivi formativi
The goal of this course is the study of the management of information in modern information systems. The course will then specifically focus on transaction management, distributed databases, data warehousing, data mining, NoSQL, and distributed computation.
Risultati apprendimento attesi
tecniche di valutazione della qualita` dei dati e preprocessing;
- tecniche di riduzione della numerosita` e della dimensionalita` dei dati;
- metodi per frequent pattern analysis e regole di associazione;
- metodi per problemi di classificazione;
- cluster analysis;
- programmazione in linguaggio R.
- tecniche di riduzione della numerosita` e della dimensionalita` dei dati;
- metodi per frequent pattern analysis e regole di associazione;
- metodi per problemi di classificazione;
- cluster analysis;
- programmazione in linguaggio R.
Periodo: Secondo semestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento non può essere seguito come corso singolo. Puoi trovare gli insegnamenti disponibili consultando il catalogo corsi singoli.
Programma e organizzazione didattica
Linea Milano - disponibile in streaming da Crema
Responsabile
Periodo
Secondo semestre
STUDENTI FREQUENTANTI
Programma
1. Transaction management (ACID properties, failure management, concurrency control)
2. Distributed databases (fragmentation and allocation, transaction management in distributed scenarios, distributed queries)
3. Data warehousing (ETL, conceptual and logical modeling)
4. Data mining techniques (e.g., itemset mining, classification, clustering)
5. NoSQL (data models, distribution models, consistency and ACID properties, distributed computation)
2. Distributed databases (fragmentation and allocation, transaction management in distributed scenarios, distributed queries)
3. Data warehousing (ETL, conceptual and logical modeling)
4. Data mining techniques (e.g., itemset mining, classification, clustering)
5. NoSQL (data models, distribution models, consistency and ACID properties, distributed computation)
Informazioni sul programma
1. Transaction management (ACID properties, failure management, concurrency control)
2. Distributed databases (fragmentation and allocation, transaction management in distributed scenarios, distributed queries)
3. Data warehousing (ETL, conceptual and logical modeling)
4. Data mining techniques (e.g., itemset mining, classification, clustering)
5. NoSQL (data models, distribution models, consistency and ACID properties, distributed computation)
2. Distributed databases (fragmentation and allocation, transaction management in distributed scenarios, distributed queries)
3. Data warehousing (ETL, conceptual and logical modeling)
4. Data mining techniques (e.g., itemset mining, classification, clustering)
5. NoSQL (data models, distribution models, consistency and ACID properties, distributed computation)
Propedeuticità
Basi di dati (Databases)
Prerequisiti
Prerequisites: None
Exam: The exam consists of a written test, including both questions and exercises covering the topics of the course. Questions and exercises are aimed at evaluating the knowledge and understanding of the student of the course.
Exam: The exam consists of a written test, including both questions and exercises covering the topics of the course. Questions and exercises are aimed at evaluating the knowledge and understanding of the student of the course.
Metodi didattici
Classes
Materiale di riferimento
STUDENTI NON FREQUENTANTI
Teaching material made available through Ariel platform (http://sforestiasd.ariel.ctu.unimi.it/v3/Home/).
Books and scientific papers indicated during classes.
Books and scientific papers indicated during classes.
Programma
1. Transaction management (ACID properties, failure management, concurrency control)
2. Distributed databases (fragmentation and allocation, transaction management in distributed scenarios, distributed queries)
3. Data warehousing (ETL, conceptual and logical modeling)
4. Data mining techniques (e.g., itemset mining, classification, clustering)
5. NoSQL (data models, distribution models, consistency and ACID properties, distributed computation)
2. Distributed databases (fragmentation and allocation, transaction management in distributed scenarios, distributed queries)
3. Data warehousing (ETL, conceptual and logical modeling)
4. Data mining techniques (e.g., itemset mining, classification, clustering)
5. NoSQL (data models, distribution models, consistency and ACID properties, distributed computation)
Prerequisiti
Prerequisites: None
Exam: The exam consists of a written test, including both questions and exercises covering the topics of the course. Questions and exercises are aimed at evaluating the knowledge and understanding of the student of the course.
Exam: The exam consists of a written test, including both questions and exercises covering the topics of the course. Questions and exercises are aimed at evaluating the knowledge and understanding of the student of the course.
Materiale di riferimento
Teaching material made available through Ariel platform (http://sforestiasd.ariel.ctu.unimi.it/v3/Home/).
Books and scientific papers indicated during classes.
Books and scientific papers indicated during classes.
Docente/i