Učni načrt predmeta

Predmet:

Poslovna inteligenca II

Course:

Business Inteligence II

Študijski program in stopnja / Study programme and level	Študijska smer / Study field	Letnik / Academic year	Semester / Semester
Informacijske in komunikacijske tehnologije, 3. stopnja	Inteligentni sistemi in robotika	1	1
Information and Communication Technologies, 3rd cycle	Intelligent Systems and Robotics	1	1

Vrsta predmeta / Course type

Izbirni / Elective

Univerzitetna koda predmeta / University course code:

IKT3-629

Predavanja Lectures	Seminar Seminar	Vaje Tutorial	Klinične vaje work	Druge oblike študija	Samost. delo Individ. work	ECTS
15	15			15	105	5

*Navedena porazdelitev ur velja, če je vpisanih vsaj 15 študentov. Drugače se obseg izvedbe kontaktnih ur sorazmerno zmanjša in prenese v samostojno delo. / This distribution of hours is valid if at least 15 students are enrolled. Otherwise the contact hours are linearly reduced and transfered to individual work.

Nosilec predmeta / Course leader:

prof. dr. Matjaž Gams

Sodelavci / Lecturers:

Jeziki / Languages:

Predavanja / Lectures:

slovenščina, angleščina / Slovenian, English

Vaje / Tutorial:

Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:

Prerequisits:

Vsebina:

Content (Syllabus outline):

Znanstvena metoda: Strukture znanstvenega védenja, znanstvene aktivnosti in procesi.

Uvod: Definicija inteligence in poslovne inteligence (BI), osnovna shema BI, kriteriji, razlogi in področja za uvajanje, problemi in pasti uvajanja, najboljše poslovne prakse, definicija poslovne analitike in primeri uporabe, pregled razlik med poslovno inteligenco in poslovno analitiko, primeri iz prakse.

Upravljanje s podatki: Podatkovna skladišča, kakovost podatkov, priprava in oplemenitenje podatkov, migracija podatkov, posredovanje podatkov, primeri največjih nevarnosti in napak.

Poslovna analitika: Odkrivanje, analiza in definiranje poslovnih problemov, inteligentno analitično modeliranje za reševanje poslovnih/tržnih problemov, ovrednotenje in prenos rezultatov v poslovno prakso, pregled tipičnih poslovnih problemov.

Strategije trženja in neposredno trženje: Poslovne strategije, planiranje in razvoj strategij, strategije neposrednega trženja, poslovni modeli, analiza trženjskih priložnosti in okolja. Analiza trga in strank, kontaktne strategije, tržni kanali, problemi integracije, personalizacija tržnih vsebin, spremljanje aktivnosti strank, upravljanje tržne
učinkovitosti, trženje na osnovi dogodkov,
trženje v realnem času.

Teorija iger in njena uporaba: Antagonistične igre s hkratnimi in zaporednimi potezami, Nashevo ravnovesje in kako ga najti, čiste in mešane strategije. Poslovna uporaba: barantanje, dražbe,
pogajanja. Računalniška simulacija.

Izzivi pri razvoju programskih sistemov in
implementacija projektov: Predstavitev celotnega procesa razvoja programskih projektov s poudarkom na reševanju problemov, na katere naletimo pri večjih projektih.

Orodja in rešitve: Pregled najboljših orodij in rešitev na trgu za BI/CI, vpogled v prihajajoče tehnologije.

Scientific Method: Scientific knowledge structures, scientific activities/processes.

Introduction: Definition of intelligence and business intelligence (BI), basic BI schema, criteria, reasons and areas for adoption, common problems and pitfalls, best practices, definition of business analytics (BA) and some use-cases, review of differences among BI and BA, best practices.

Data handling: Data warehousing, data quality, data preparation/enhancement, data migration, data mediation, examples of major pitfalls.

Predictive business analytics: Business problem detection, analysis, and definition, analytical modeling for solving business/marketing problems, evaluation and business adoption of modeling results, overview of various industry.

Marketing strategies and direct marketing: Business strategies, strategy planning and
development, direct marketing strategies (product, offer, media, distribution and creative
strategies), business models, analysis of marketing opportunities and environment. Customer/market analysis and research, contact
strategies, marketing channels, integration aspects, creative tactics, content personalization,
response tracking, marketing performance management, event-driven marketing, real-time marketing, best practice examples in various
industries.

Game theory and its applications: Simultaneous-move (static) and sequential-move (dynamic) non-cooperative games, Nash equilibrium and how to find it, pure and mixed strategies. Business applications: bargaining, auctions, negotiations.

Challenges in software engineering and project
implementation: A detailed overview of development of software project with the emphasis on understanding problems that are specific to big software projects.

Tools and Solutions: Overview of best-of-breed BI/CI tools and solutions in the marketplace, insight into emerging technologies.

Temeljna literatura in viri / Readings:

Cilji in kompetence:

Objectives and competences:

Predvideni študijski rezultati:

Intendeded learning outcomes:

Metode poučevanja in učenja:

Learning and teaching methods:

Načini ocenjevanja:

Delež v % / Weight in %

Assesment:

Seminarska naloga

80 %

Seminar work

Ustni zagovor

20 %

Oral defense

Reference nosilca / Lecturer's references:

1.	V. Vidulin, M. Bohanec, and M. Gams. “Combining human analysis and machine data mining to obtain credible data relations.” Information sciences, vol. 288, pp. 254-278, 2014.
2.	A. Pivk, O. Vasilecas, D. Kaliatiene, and R. Rupnik. “On approach for the implementation of data mining to business process optimisation in commercial companies.” Technological and economic development of economy, vol. 19, no. 2, pp. 237-256, 2013.
3.	D. Zupančič, M. Luštrek, and M. Gams. “Multi-agent architecture for control of heating and cooling in a residential space.” The Computer journal, ISSN 0010-4620, 2014.
4.	B. Pogorelc, E. Stojmenova, M. Gams et al. “Ambient bloom: new business, content, design and models to increase the semantic ambient media experience.” Multimedia tools and applications, vol. 66, no. 1, pp. 7-32, 2014.
5.	M. Gams, H. Gjoreski, M. Luštrek, B. Kaluža, Metoda in sistem za prepoznavanje aktivnosti na podlagi konteksta : patent SI 23356 A. Ljubljana: Urad RS za intelektualno lastnino, 28. nov. 2014. [COBISS.SI-ID 27964199] - patent.