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A course is the basic teaching unit, it's design as a medium for a student to acquire comprehensive knowledge and skills indispensable in the given field. A course guarantor is responsible for the factual content of the course.
For each course, there is a department responsible for the course organisation. A person responsible for timetabling for a given department sets a time schedule of teaching and for each class, s/he assigns an instructor and/or an examiner.
Expected time consumption of the course is expressed by a course attribute extent of teaching. For example, extent = 2 +2 indicates two teaching hours of lectures and two teaching hours of seminar (lab) per week.
At the end of each semester, the course instructor has to evaluate the extent to which a student has acquired the expected knowledge and skills. The type of this evaluation is indicated by the attribute completion. So, a course can be completed by just an assessment ('pouze zápočet'), by a graded assessment ('klasifikovaný zápočet'), or by just an examination ('pouze zkouška') or by an assessment and examination ('zápočet a zkouška') .
The difficulty of a given course is evaluated by the amount of ECTS credits.
The course is in session (cf. teaching is going on) during a semester. Each course is offered either in the winter ('zimní') or summer ('letní') semester of an academic year. Exceptionally, a course might be offered in both semesters.
The subject matter of a course is described in various texts.

BI-BIG.21 DB Technologies for Big Data Extent of teaching: 2P+2C
Instructor: Borkovcová M. Completion: KZ
Department: 18102 Credits: 5 Semester: Z,L

Annotation:
Students will be introduced into the field of Big Data processing where nonrelational (NoSQL) database engines are typically used today. The course is focused practically so that after finishing the course students were able to choose suitable tools (mostly open source) and techniques,design and implement a simplest reproducible method of data processing (data collection, transformation/aggregation, presentation). Students get acquainted with various architectures for processing and storing big data. A theoretical foundation and presentation of individual technologies will be supplemented with specific examples from practice.

Lecture syllabus:
1. Introduction to the subject, distributed solutions, basic concepts (Big Data, cluster, distributed file systems, CAP theorem,...)
2. NoSQL key-value database (Redis)
3. NoSQL document database (MongoDB)
4. NoSQL columnar database (Apache Cassandra)
5-6. NoSQL graph database (Neo4j) 7-9. The Elastic Stack (Elasticsearch, Beats, Logstash, Kibana)
10. Hadoop Ecosystem (Hadoop, Map Reduce, HDFS, YARN)
11-12. Apache Spark
13. The Credit test

Seminar syllabus:
1. Introduction to the laboratory environment
2. Introduction to working with Cassandra Cluster
3. Basics of Redis
4. MongoDB Basics
5. Basics of Apache Cassandra
6. Basics of Neo4j
7. Basics of Elasticsearch
8. Ways and possibilities of data presentation using ELK Stack
9. Basics of working with Apache Spark, use of the Scala language
10. Practical workshop on a selected topic
11. Consultation on semester work
12. Defense of semester work - 1st part
13. Defense of semester work - 2nd part

Literature:
1. Holubová Irena, Minařík Karel, Novák David, Kosek Jiří. Big Data a NoSQL databáze. 2015. ISBN 978-80-247-5466-6.
2. Meier A., Kaufmann M. : SQL & NoSQL Databases. Springer, 2019. ISBN 978-3-658-24549-8.
3. Bradshaw S., Brazil E., Chodorow Ch. : MongoDB: The Defnitive Guide: Powerful and Scalable Data Storage. O'Reilly Media, 2019. ISBN 9781491954461.
4. https://redis.io
5. https://cassandra.apache.org/
6. https://neo4j.com/
7. https://www.mongodb.com/
8. https://www.elastic.co/

Requirements:
Basic knowledge of relational databases, working with the command line, knowledge of Docker technology is recommended.

The course is also part of the following Study plans:
Study Plan Study Branch/Specialization Role Recommended semester
BI-MI.21 Business Informatics 2021 (In Czech) V 6
BI-SI.21 Software Engineering 2021 (in Czech) V 6
BI-PI.21 Computer Engineering 2021 (in Czech) V 6
BI-IB.21 Information Security 2021 (in Czech) V 6
BI-UI.21 Artificial Intelligence 2021 (in Czech) PV 5
BI-PV.21 Computer Systems and Virtualization 2021 (in Czech) V 6
BI-TI.21 Computer Science 2021 (in Czech) V 6
BI-WI.21 Web Engineering 2021 (in Czech) PS 6
BI-SPOL.21 Unspecified Branch/Specialisation of Study VO 6
BI-PS.21 Computer Networks and Internet 2021 (in Czech) V 6
BI-PV.21 Computer Systems and Virtualization 2021 (in Czech) PV 6
BI-UI.21 Artificial Intelligence 2021 (in Czech) V 6
BI-PG.21 Computer Graphics 2021 (in Czech) V 6


Page updated 28. 3. 2024, semester: Z/2023-4, L/2019-20, L/2022-3, Z/2019-20, Z/2022-3, L/2020-1, L/2023-4, Z/2020-1, Z,L/2021-2, Send comments to the content presented here to Administrator of study plans Design and implementation: J. Novák, I. Halaška