logo
Item card
logo

Business intelligence - business use of data warehouses

Some basic information about the module

Cycle of education: 2019/2020

The name of the faculty organization unit: The faculty Mathematics and Applied Physics

The name of the field of study: Engineering and data analysis

The area of study: sciences

The profile of studing:

The level of study: first degree study

Type of study: full time

discipline specialities :

The degree after graduating from university: engineer

The name of the module department : Department of Electrical and Computer Fundamentals

The code of the module: 12331

The module status: mandatory for teaching programme

The position in the studies teaching programme: sem: 4 / W15 L15 / 2 ECTS / Z

The language of the lecture: Polish

The name of the coordinator 1: Witold Posiewała, PhD, Eng.

The name of the coordinator 2: Bogdan Kwiatkowski, PhD, Eng.

The aim of studying and bibliography

The main aim of study: Concept of data warehouse, OLAP architecture and issues related to Data Manning. Introduction of key concepts, definitions and areas of Business Intelligence applications. Architecture of the Business Intelligence system.

The general information about the module: The subject discusses the construction of decision support systems, technology of multidimensional data sources and interfaces of such systems.

Bibliography required to complete the module
Bibliography used during lectures
1 Pelikant A. Hurtownie danych. Od przetwarzania analitycznego do raportowania Helion. 2011
2 Surma J. Business Intelligence. Systemy wspomagania decyzji biznesowych PWN. 2010
3 Ch. Todman Projektowanie hurtowni danych WNT, Warszawa. 2003

Basic requirements in category knowledge/skills/social competences

Formal requirements: The student satisfies the formal requirements set out in the study regulations.

Basic requirements in category knowledge: He knows the relational databases, has basic knowledge about the functioning of web applications.

Basic requirements in category skills: He can use the SQL language. He can detect and use relationships in database tables.

Basic requirements in category social competences: He can participate in laboratory classes.

Module outcomes

MEK The student who completed the module Types of classes / teaching methods leading to achieving a given outcome of teaching Methods of verifying every mentioned outcome of teaching Relationships with KEK Relationships with PRK
01 He knows what data warehouses are and can use open source tools to create them. lecture / lab observation of performance, pass K_W06+
K_U07+
K_K02+
P6S_KK
P6S_KO
P6S_UW
P6S_WG
02 He knows the concept of a multidimensional data source and can create it lecture / lab observation of performance, pass K_W07+
K_U07+
P6S_UW
P6S_WG
03 He knows the key concepts, definitions and areas of Business Intelligence applications lecture pass K_W11+
K_U17+
K_U18+
K_K02+
P6S_KK
P6S_KO
P6S_UW
P6S_WK
04 He is able to use the reporting and analytical application lecture / lab observation of performance, pass K_W07+
K_U07+
K_K02+
P6S_KK
P6S_KO
P6S_UW
P6S_WG

Attention: Depending on the epidemic situation, verification of the achieved learning outcomes specified in the study program, in particular credits and examinations at the end of specific classes, can be implemented remotely (real-time meetings).

The syllabus of the module

Sem. TK The content realized in MEK
4 TK01 The concept of data warehouse, data warehouse architecture W1 MEK01
4 TK02 Warehouse design and integration of source data. W2,L1-3 MEK01 MEK02
4 TK03 Multidimensional OLAP data sources, multidimensional data models. OLAP operations. W3,W4,L4-5 MEK01 MEK02
4 TK04 The language of MDX SQL queries W5,L6 MEK02 MEK03
4 TK05 Architecture of the Business Intelligence system. Methodology for implementing the BI system. W6 MEK03
4 TK06 Reporting and analytical applications. W7,L7 MEK04
4 TK07 Warehouse creation tools - data conversions, data replenishment, data analysis in a data warehouse, defining relationships - PostgreSQL database. Installation and configuration of the OLAP engine - Mondrian, creating and executing MDX queries, PostgreSQL as XMLA datasource, JPivot library, creating your own BI website. L1-L7 MEK01 MEK02 MEK03 MEK04

The student's effort

The type of classes The work before classes The participation in classes The work after classes
Lecture (sem. 4) The preparation for a test: 20.00 hours/sem.
contact hours: 15.00 hours/sem.
Laboratory (sem. 4) contact hours: 15.00 hours/sem.
Advice (sem. 4) The participation in Advice: 2.00 hours/sem.
Credit (sem. 4) The preparation for a Credit: 4.00 hours/sem.
The written credit: 2.00 hours/sem.

The way of giving the component module grades and the final grade

The type of classes The way of giving the final grade
Lecture Assessment issued on the basis of credit / test.
Laboratory Assessment based on observation of performance and pass / test.
The final grade

Sample problems

Required during the exam/when receiving the credit
(-)

Realized during classes/laboratories/projects
(-)

Others
(-)

Can a student use any teaching aids during the exam/when receiving the credit : no

The contents of the module are associated with the research profile: no