Course detail

Data Warehousing

FP-DS_2Acad. year: 2019/2020

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.

Learning outcomes of the course unit

Students understand the importance of data warehouses, OLAP techniques and data mining and are able to use it.

Prerequisites

Database systems

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Lacko, L.: Datové sklady, analýza OLAP a dolování dat. Computer Press, 2003, 488 s. ISBN 80-7226-969-0 (CS)
Ponniah, P.: Data Warehousing Fundamentals. John Wiley & Sons, Inc., 2001, 516 s. ISBN 0-471-41254-6 (EN)
Humphries, M., Hawkins, M. W. a kol.: Data warehousing, Principy a praxe. Computer Press, 2002, 256 s. ISBN 8072265601. (EN)

Planned learning activities and teaching methods

The course contains lectures that explain basic principles, problems and methodology of the discipline, and exercises that promote the practical knowledge of the subject presented in the lectures.

Assesment methods and criteria linked to learning outcomes

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.

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

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.

Seminars:
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.

Aims

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.

Specification of controlled education, way of implementation and compensation for absences

Design and presentation of projects in due dates. Students can work on the projects in their own free time.

Classification of course in study plans

  • Programme BAK-MIn Bachelor's

    branch BAK-MIn , 3. year of study, winter semester, 4 credits, compulsory

Type of course unit

 

Lecture

13 hours, optionally

Teacher / Lecturer

Computer-assisted exercise

26 hours, compulsory

Teacher / Lecturer

eLearning