Big Data Technology

Laboratory Of Big Data And Artificial Intelligence For Society

Credits: 
4
Hours: 
48
Area: 
Big Data Technology
Description: 

In this module groups of students will be guided to design and develop an entire project in Big Data and AI: from data collection to the final delivery. The students will employ in the project methods, techniques and tools studied in the other modules. The duration of this module, differently from the others, will span across several months until the end of the lectures when the results of the project will be presented in front of a committee.

Data Management For Business Intelligence

Credits: 
2
Hours: 
24
Area: 
Big Data Technology
Academic Year: 
Description: 

The module presents the methodological aspects, technologies and systems for designing, populating and querying Data Warehouses for decision support. The emphasis is placed on the analysis of application problems using examples and case studies, with laboratory exercises.

Prerequisites: knowledge of basic SQL, Excel, Python programming.

Alignment

Credits: 
5
Hours: 
60
Area: 
Big Data Technology
Description: 

The module has the aim to align the students' competences in computer science and in basic analytics, especially in data bases, and Python programming for data science. Starting form a theoretical introduction to the basics of programming and relational database modelling the course will be focused on pratical lectures for learning to query and modelling databases and to solving problems by writing Python programs in both static and dynimic environments. This module is based on hands-on work

High Performance & Scalable Analytics, NO-SQL Big Data Platforms

Credits: 
2
Hours: 
22
Area: 
Big Data Technology
Teachers: 
Academic Year: 
Description: 

This course aims at teaching the basic theoretical concepts behind the MapReduce distributed computing paradigm, and Hadoop in particular, and at building expertise in the practical usage of high-performance computing tools for data engineering, analysis and mining. In particular, the students will learn how classical data mining algorithms can be applied to Big Data using Hadoop (Spark). Real (and open source) datasets will be used to present examples and to let the students build their own projects.

Data Management for Business Intelligence

Credits: 
2
Hours: 
20
Area: 
Big Data Technology
Description: 

The module presents technologies and systems for designing, populating and querying Data Warehouse for decision support. The emphasis is on technologies and analysis of application problems by using examples and case studies. The student will acquire knowledge and skills on major technologies for Business Intelligence such as ETL (Extract, Transform and Load), Data Warehousing, Analytics SQL, OLAP (Online Analytical Processing).

High Performance & Scalable Analytics, NO-SQL Big Data Platforms

Credits: 
2
Hours: 
22
Area: 
Big Data Technology
Teachers: 
Academic Year: 
Description: 

This course aims at teaching the basic theoretical concepts behind the MapReduce distributed computing paradigm, and Hadoop in particular, and at building expertise in the practical usage of high-performance computing tools for data engineering, analysis and mining. In particular, the students will learn how classical data mining algorithms can be applied to Big Data using Hadoop (Spark). Real (and open source) datasets will be used to present examples and to let the students build their own projects.

High Performance & Scalable Analytics, NO-SQL Big Data Platforms

Credits: 
2
Hours: 
22
Area: 
Big Data Technology
Description: 

The aim of this course is to introduce the student with the high performance Big Data management tools. The student will gain expertise in the use od NO-SQL platforms for the analysis and mining of large data volumes, thus performing tasks that would not be feasible with traditional data bases.

High Performance & Scalable Analytics, NO-SQL Big Data Platforms

Credits: 
2
Hours: 
20
Area: 
Big Data Technology
Teachers: 
Academic Year: 
Description: 

The aim of this course is to introduce the student with the high performance Big Data management tools. The student will gain expertise in the use od NO-SQL platforms for the analysis and mining of large data volumes, thus performing tasks that would not be feasible with traditional data bases.

Data Management for Business Intelligence

Credits: 
2
Hours: 
20
Area: 
Big Data Technology
Academic Year: 
Description: 

The module shows technologies and systems for accessing, managing and analysing Big Data for decision support. Technologies and analysis of problems are shown using examples and case studies in lab. The student will acquire skills on the main technologies for business intelligence and big data management, including data warehouse and online analytical processing technologies.

Data Management for Business Intelligence

Credits: 
2
Hours: 
20
Area: 
Big Data Technology
Description: 

The module presents technologies and systems for designing, populating and querying Data Warehouse for decision support. The emphasis is on technologies and analysis of application problems by using examples and case studies. The student will acquire knowledge and skills on major technologies for Business Intelligence such as ETL (Extract, Transform and Load), Data Warehousing, Analytics SQL, OLAP (Online Analytical Processing).

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