BSc: Advanced Databases

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Advanced Databases

  • Course name: Advanced Databases
  • Course number: XYZ
  • Knowledge area: Data Science

Course characteristics

Administrative details

  • Faculty: Computer Science and Engineering
  • Year of instruction: 4th year of BS
  • Semester of instruction: 2nd semester
  • No. of Credits: 4 ECTS
  • Total workload on average: 144 hours overall
  • Class lecture hours: 2 per week
  • Class tutorial hours: 0 per week
  • Lab hours: 4 per week
  • Individual lab hours: 0
  • Frequency: weekly throughout the semester
  • Grading mode: letters: A, B, C, D

Prerequisites

  • Data Modelling and Databases I
  • Data Modelling and Databases II
  • Data Structures and Algorithms I
  • Data Structures and Algorithms II
  • Discrete Math and Logic
  • Introduction to Programming I
  • Introduction to Programming II

Key concepts of the class

Data Modelling and Databases I and II mostly focus on the relational model, its design and the implementation details of RDBMS. This course is focused on alternative paradigms, generally defined under the hat of NoSQL, and parallel and distributed architectures with all the theoretical and practical consideration of the case.

Expected learning outcomes

  • Devise appropriate ways to store and index data
  • Use persistency tools in the context of modern software architectures and the Cloud
  • Understanding of NoSQL and CAP theorem
  • Fluency with Graph DB and relatd query languages
  • Understanding parallel and distributed databases

Expected acquired core competences

  • Software Design
  • Software Engineering
  • Software Construction
  • Relational Databases
  • Data Modeling
  • Database Design
  • Database Systems
  • Query Languages: Implementation and Optimization
  • Implementation of Database Systems
  • Indexing
  • Information Storage and Retrieval
  • NoSQL
  • Document-based databases
  • Graph databases
  • Non-relational query languages
  • Theory of distributed systems
  • Algorithms for distributed systems
  • CAP theorem
  • Parallel and distributed databases
  • MapReduce

Course evaluation

Course grade breakdown
Proposed points
Assignments and project 30 40
Mid-term Exam 30 30
Written Final 40 30

Reference and referecnce material

  • Lecturing and lab slides and material will be provided
  • Several resources are available online and will be pointed during the course

Textbook

Required computer resources

Students should have laptops.

Course Sections

Section 1

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Topics covered in this section:

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Typical questions for ongoing performance evaluation within this section

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Section 2

Section title:

Topics covered in this section:

What forms of evaluation were used to test students’ performance in this section?

Typical questions for ongoing performance evaluation within this section

Typical questions for seminar classes (labs) within this section

Test questions for final assessment in this section