Corso di laurea magistrale in Data Science
Facoltà di Ingegneria dell'Informazione, Informatica e Statistica, Sapienza Università di Roma

Data Management for Data Science


Prof. Riccardo Rosati


Course contents and objectives

The main goal of the course is to present the basic concepts of data management systems. The first part of the course introduces the main aspects of relational database systems, including basic functionalities, file and index organizations, and query processing. The second part of the course aims at presenting the main non-relational approaches to data management, in particular, multidimensional data management, large-scale data management, and open data management.

Course program

  1. Introduction to relational databases
  2. The structure of a Data Base Management System
  3. Physical structures for data
  4. Large-scale data management
  5. Open data management


The lectures for a.y. 2017/2018 were held in the second semester (from February 26, 2018 to June 1, 2018), with the following schedule:

Course material

  1. Introduction to relational databases
  2. SQL
  3. Exercise on SQL
  4. DBMS transaction management and recovery management
  5. DBMS file organization
  6. DBMS query evaluation
  7. Introduction to big data and data warehouses
  8. Graph databases
  9. Exercise on file organization and query evaluation
  10. NoSQL aggregated databases
  11. The MongoDB system
Other useful references:



The written exam is a set of exercises and questions about all the course topics (time to complete the exam: 2 hours).

The students who presented all the homeworks during the lectures do not have to take the written exam: please see the page on homework results for more details.

Exam dates:

As usual, before every exam date, students MUST reserve for the exam on Infostud. The reservation deadline is 3 or 4 days before the exam date.

The students who presented all the homeworks during the lectures have to follow the instructions on the page on homework results to register their grade.

Schedule and contents of past lectures

Link to the website of the 2016/2017 edition of this course