INMNPDTS Data Warehouse

School of Business Administration in Karvina
Winter 2019
Extent and Intensity
2/1/0. 4 credit(s). Type of Completion: zk (examination).
Teacher(s)
Mgr. Milena Janáková, Ph.D. (lecturer)
Mgr. Milena Janáková, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. František Koliba, CSc.
Department of Informatics and Mathematics – School of Business Administration in Karvina
Contact Person: Ing. Jan Górecki, Ph.D.
Timetable
Wed 13:05–14:40 A406
  • Timetable of Seminar Groups:
INMNPDTS/01: Wed 14:45–15:30 A406, M. Janáková
Prerequisites
FAKULTA(OPF) && TYP_STUDIA(N) && FORMA(P)
None; Excluded courses - INF/PDTS
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 15 student(s).
Current registration and enrolment status: enrolled: 0/15, only registered: 0/15
fields of study / plans the course is directly associated with
Course objectives
The aim of the course is to provide an overview about advanced database technologies such as data warehouse, OLAP analysis and data mining. There is primarily described management, planning, design with implementation and management of a specific project database or data warehouse.
Syllabus
  • 1st Introduction to data warehousing.
    2nd The transition from relational databases to multidimensional.
    3rd Tools for working with the administration and analytical services.
    4th Data warehouses.
    5th Methods for building a data warehouse.
    6th Preparing data - ETL phase.
    7th OLAP analysis.
    8th OLAP.
    9th OLAP over data from Oracle DB.
    10th Administration access to OLAP databases.
    11th Data mining.
    12th Model for process of data mining.
    13th Selection of algorithm and model.
Literature
    required literature
  • LACO, L. Datové sklady analýza OLAP a dolování dat 2003. Computer Press, Brno. ISBN 80-7226-969-0. info
  • KIMBAL, R., ROSS, M. The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. Indianapolis, John Wiley & Sons, 2013. ISBN -13: 978-11185308. info
  • INMON, W. H. Building the Data Warehouse. Indianapolis, Wiley Publishing, 2005. ISBN -13: 978-07645994. info
  • BERKA Petr. Dobývání znalostí z databází. Praha, 2003. ISBN 80-200-1062-9. info
    recommended literature
  • LIEBOWITZ, J. Big Data and Business Analytics. NW, CRC Press, 2013. ISBN -13: 978-14665657. info
  • KRISHNAN, K. Big Data and Business Analytics. NW, CRC Press, 2013. ISBN 0124058914. info
  • Šarmanová, J. Informační systémy a datové sklady. VŠB - Technická univerzita Ostrava, 2007. ISBN 978-80-248-1500-8. URL info
  • HUMPHRIES, M.,HAWKINS,M.W.,Dy M.C. Data warehousing, Návrh a implementace. Brno, Computer Presss, 2002. ISBN 80-72-2656-0. info
  • Olivia Parr Rud. Data Mining. Computer Press, Praha, 2001. ISBN 80-7226-577-6. info
Teaching methods
Skills demonstration
Seminar classes
Assessment methods
Grade
Language of instruction
Czech
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
Teacher's information
attendance in seminars 50%, seminar paper, ongoing test, final combined exam
ActivityDifficulty [h]
Ostatní studijní zátěž39
Přednáška26
Seminář13
Zkouška40
Summary118
The course is also listed under the following terms Winter 2014, Winter 2015, Winter 2016, Winter 2017, Winter 2018.
  • Enrolment Statistics (recent)
  • Permalink: https://is.slu.cz/course/opf/winter2019/INMNPDTS