Course: Advanced Database Systems

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Course title Advanced Database Systems
Course code AUPKS/AE7PD
Organizational form of instruction Lecture + Lesson
Level of course Master
Year of study not specified
Semester Winter
Number of ECTS credits 4
Language of instruction English
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Course availability The course is available to visiting students
Lecturer(s)
  • Prokopová Zdenka, doc. Ing. CSc.
  • Šilhavý Petr, doc. Ing. Ph.D.
  • Komenda Tomáš, Ing.
  • Beltran Prieto Luis Antonio, MSc.
Course content
- Introduction to "advanced" databases - from SQL to NoSQL - Principles of NoSQL databases - scalability, sharding, replication etc. - Distributed data processing - MapReduce - Key-value NoSQL database - Document NoSQL databases - Column NoSQL databases - Graph NoSQL databases - Multi-model databases - Other Big Data processing options - Query languages in NoSQL - MongoDB - installation and configuration - MongoDB - basic operations, creation and use of indexes - MongoDB - support for database aggregation and modeling - MongoDB - management and use of roles and users, regular expressions

Learning activities and teaching methods
Monologic (Exposition, lecture, briefing), Dialogic (Discussion, conversation, brainstorming), Demonstration, Exercises on PC, Practice exercises
prerequisite
Knowledge
Knowledge from relational database systems - relational model, normal forms, SQL language, data security.
Knowledge from relational database systems - relational model, normal forms, SQL language, data security.
learning outcomes
define the concept of Big Data
define the concept of Big Data
characterize the methods of distributed data processing
characterize the methods of distributed data processing
explain the principle of the CAP theorem
explain the principle of the CAP theorem
list the different types of NoSQL databases
list the different types of NoSQL databases
describe other BigData processing options
describe other BigData processing options
Skills
design a document database model
design a document database model
install and configure MongoDB
install and configure MongoDB
create a database, a collection, a document and save the document to the collection
create a database, a collection, a document and save the document to the collection
find the required data by querying
find the required data by querying
apply the use of indexes, MapReduce, Replication
apply the use of indexes, MapReduce, Replication
teaching methods
Knowledge
Dialogic (Discussion, conversation, brainstorming)
Dialogic (Discussion, conversation, brainstorming)
Monologic (Exposition, lecture, briefing)
Demonstration
Demonstration
Practice exercises
Practice exercises
Exercises on PC
Exercises on PC
Monologic (Exposition, lecture, briefing)
assessment methods
Systematic observation of the student
Analysis of the student's performance
Systematic observation of the student
Written examination
Written examination
Grade (Using a grade system)
Oral examination
Oral examination
Analysis of the student's performance
Grade (Using a grade system)
Recommended literature
  • BANKER, K., et al. MongoDB in action.. New York, 2016.
  • EDWARD, S.G. Practical MongoDb : architecting, developing, and administering MongoDB. Expert's voice in open source.. New York, 2015.
  • ERL, Thomas; KHATTAK, Wajid; BUHLER, Paul. Big Data Fundamentals. New York, 2016.
  • HOLUBOVÁ, Irena, et al. Big Data a NoSQL databáze.. Praha, 2015.
  • PLUGGE, E., et al. The Definitive Guide to MongoDB: A complete guide to dealing with Big Data using MongoDB.. New York, 2015.
  • SADALAGE, Pramod J.; FOWLER, Martin. NoSQL distilled: a brief guide to the emerging world of polyglot persistence.. Pearson Education, 2013.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester