Information Management
A.Y. 2018/2019
Learning objectives
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.
Expected learning outcomes
- techniques for data quality evaluation and preprocessing
- techniques for numerosity and dimensionality reduction in data;
- methods for frequent pattern analysis and association rules;
- methods for classification problems;
- cluster analysis;
- R language programming.
- techniques for numerosity and dimensionality reduction in data;
- methods for frequent pattern analysis and association rules;
- methods for classification problems;
- cluster analysis;
- R language programming.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Linea Milano - disponibile in streaming da Crema
Responsible
Lesson period
Second semester
ATTENDING STUDENTS
Course syllabus
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)
Website
NON-ATTENDING STUDENTS
Course syllabus
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)
Professor(s)