Course details
Data Warehousing
DS_2 Acad. year 2024/2025 Winter semester 5 credits
Basic terms: relational and multidimensional database model, operational database, data warehouse, data mart, building and running of a data warehouse, modelling a data warehouse - multidimensional model, data cube, OLAP analysis, data mining.
Guarantor
Language of instruction
Completion
Time span
- 13 hrs lectures
- 26 hrs exercises
Assessment points
- 60 pts final exam (written part)
- 20 pts mid-term test (written part)
- 20 pts seminars in computer labs
Department
Lecturer
Instructor
Learning objectives
Understanding the basic theory of data warehouses and acquirement of practical skills in their design and usage, understanding the basics of OLAP techniques and data mining.
Students understand the importance of data warehouses, OLAP techniques and data mining and are able to use it.
Prerequisite knowledge and skills
Database systems
Fundamental literature
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Ponniah, P.: Data Warehousing Fundamentals. John Wiley & Sons, Inc., 2001, 516 s. ISBN 0-471-41254-6
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Humphries, M., Hawkins, M. W. a kol.: Data warehousing, Principy a praxe. Computer Press, 2002, 256 s. ISBN 8072265601.
Syllabus of lectures
1. Basic terms of data warehousing. Relationship of data warehouses and operational databases.
2. Architecture of a data warehouse. Modelling of data warehouses.
3. ETL process during creating data warehouse.
4. OLAP tachnics and OLAP operations over a data cube.
5. A case study about using of data warehouses.
6. Introduction to the design of data warehouses.
7. Introduction to data mining in data warehouses.
Syllabus of numerical exercises
1. Repetition of relational databases and SQL.
2. Data warehousing and OLAP usage analysis in Microsoft tools.
3. Use MS Excel for OLAP analysis.
4. Individual project to create a data warehouse.
5. Use of methods data mining tools in an environment of Microsoft.
6. Individual project on data mining.
Progress assessment
During the semester, students can obtain up to 40 points, including 20 points from the mid-term test consisting of questions and examples of the themes of the first half of the semester and 20 points from the projects to exercise (one to create a data warehouse and OLAP usage techniques and the other on data mining). On the credit you need to get 20 points. Final written exam for 60 points includes all topics covered in lectures and in seminars.
Design and presentation of projects in due dates. Students can work on the projects in their own free time.
Schedule
Day | Type | Weeks | Room | Start | End | Capacity | Lect.grp | Groups | Info |
---|---|---|---|---|---|---|---|---|---|
Mon | lecture | odd week | IO/E337 | 09:00 | 10:50 | 110 | Bartík | ||
Thu | exercise | 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13. of lectures | N204 N205 | 08:00 | 09:50 | 20 | FIT | ost | Bartík |
Thu | exercise | 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13. of lectures | N204 N205 | 10:00 | 11:50 | 20 | FIT | ost | Bartík |
Thu | exercise | 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13. of lectures | N204 N205 | 12:00 | 13:50 | 20 | FIT | ost | Bartík |