Data Management Systems

Recommended Prerequisites

Databases, Python programming.

Teaching Methods

Theoretical classes with detailed presentation, using audiovisual means, of the concepts, principles and fundamental theories and solving of basic practical exercises to illustrate the practical interest of the subject and exemplify its application to real cases. Laboratory classes where practical aspects are exercised.

Learning Outcomes

This curricular unit main goal is to provide students with important advanced knowledge on data management and data management systems. After attending this course, the student should understand how modern data management systems work, how to deal with bigdata and how to analyze data to reach conclusions - data science.

Work Placement(s)

No

Syllabus

1. Architectures of traditional and modern data management systems

2. Physical structures and advanced indexing, processing and optimization

3. Transactions, backups and recovery, availability.

4. Architectures for Parallel and Distributed Processing

5. Advanced data management systems (tensorflow, map-reduce, zip, vertical, no-sql, zip)

6. Data analysis using modern systems (data science).

7. Possible research topics.

Head Lecturer(s)

Pedro Nuno San-Bento Furtado

Assessment Methods

Assessment
Project: 20.0%
Exam: 80.0%

Bibliography

Ramakrishnan, Raghu, and Johannes Gehrke. Database management systems. McGraw Hill, 2000.

Silberschatz, Abraham, Henry F. Korth, and Shashank Sudarshan. Database system concepts. Vol. 4. New York: McGraw-Hill, 1997.

Ramsundar, Bharath, and Reza Bosagh Zadeh. TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning. " O'Reilly Media, Inc.", 2018.

Géron, Aurélien. Hands-on machine learning with Scikit-Learn and TensorFlow: concepts, tools, and techniques to build intelligent systems. " O'Reilly Media, Inc.", 2017.

Richert, Willi. Building machine learning systems with Python. Packt Publishing Ltd, 2013.

Raschka, Sebastian. Python machine learning. Packt Publishing Ltd, 2015.

Papers describing mechanisms on each subject, available in the course site

Course Slides made by teacher and available in the course site

Internet-available manuals

Tutorials prepared by the teacher for lab classes.