Sistemi upravljanja znanjem. Prof. dr Jelica Trninić
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1 Sistemi upravljanja znanjem Prof. dr Jelica Trninić
2 Sadržaj 1. Uvod 2. Uvod i kratka hronologija razvoja upravljanja znanjem 3. Pojmovni i teorijski aspekti upravljanja znanjem 4. Procesni aspekti upravljanja znanjem 5. Tehnološki aspekti upravljanja znanjem 6. Organizacioni aspekti upravljanja znanjem
3 Sadržaj 7. Upravljački aspekti upravljanja znanjem 8. Implementacioni aspekti upravljanja znanjem 9. Sistemi upravljanja znanjem Definicija sistema upravljanja znanjem Koje funkcionalnosti integriše sistem upravljanja znanjem? Sled uvođenja funkcija sistema upravljanja znanjem Neki primeri alata i sistema upravljanja znanjem Organički pristup u razvijanju sistema upravljanja znanjem
4 Upravljanje podacima: Kritični faktori uspešnosti Teškoće i proces Izvori podataka i kolektiranje Kvalitet podataka Multimedija i objektno-orijentisane baze podataka Upravljanje dokumentima (Document management)
5 Teškoće i proces: teškoće Eksponencijalno pocećavanje količine podataka Podaci: višestruki izvori Mali delovi podataka pogodni za specifična odlučivanja Povećana potreba za eksternim podacima
6 Teškoće i proces: teškoće Različiti zakonski zahtevi u različitim zemljama Izbor alata za upravljanje podacima veliki broj Zaštita podataka, kvalitet, i integritet
7 Teškoće i proces: proces životnog ciklusa podataka i otkrivanje znanja Kolektiranje podataka Smeštanje pohranjivanje u baze podataka Procesuiranje Pohranjivanje u data warehouse transformacija priprema za analizu Alati rudarenja - Data mining tools - knowledge Prezentiranje
8 Izvori podataka i kolektiranje Interni podaci Personalni podaci Eksterni podaci Internet and servisi komercijalnih baza podataka Metodo za kolektiranje izvornih (sirovih) podataka
9 Data Quality (DQ) Kvalitet podataka Suština i svojstva DQ: tačnost, objektivnost, verovatnost, i reputacija dostupnost DQ: dostupnost obezbeđenje zaštite
10 Data Quality (DQ) Kvalitet podataka Kontekst DQ: relevantnost, dodatana vrednost, trajnost, obuhvatnost Predstavljanje - prikazivanje DQ: lako tumačenje, razumljivost, koncizno prikazivanje, i dosledna reprezentacija
11 Multimedija i objektnoorijentisane baze podataka Objektno-orijentisane baze podataka Object-Oriented database (multimedia database) Upravljanje dokumentima - Document management
12 Data Warehousing, Mining, and Analysis Transakcije nasuprot analitičkoj obradi (processing) Data warehouse i martovi podataka Otkrivanje znanja, analiza i rudarenje
13 ...dobar sistem za isporuku podataka Lak pristup podacima od strane krajnjeg korisnika Brže donošenje odluka Tačnost i efektivnost donošenja odluka Fleksibilnost u donošenju odluka
14 Rešenja Poslovna reprezentacija podataka krajnjim korisnicima Klijent-server okruženje upiti krajnjih korisnika i sposobnost izveštavanja Repozitorijum zasnovan na serveru - Server-based repository (data warehouse)
15 Data Warehouse i Martovi podataka Namena data warehouse je da ustanovi repozitorij (spremište) podataka koji omogućava pristup operacionalnim podacima u formi prihvatljivoj za aktivnosti analitičke obrade (procesuiranje)... Data mart je rezervisan za funkcionalne ili regionalne oblasti.
16 Karakteristike - Data Warehousing Organizacija Konzistentnost Vremenska varijantnost Postojanost Relacije (veze i odnosi)
17 Koristi Troškovi Data Warehouse i Martovi podataka Arhitektura Postavljanje data warehouse na internet Prikladnost
18 Otkrivanje znanja, analize i rudarenje Osnove otkrivanja znanja u BPknowledge discovery in databases (KDD) Alati i tehnike za KDD Online analytical processing (OLAP) Data mining
19 Osnove - Knowledge Discovery in Databases (KDD) Prikupljanje ogromnog broja podataka Snažni računarski multiprocesori Data mining algoritmi
20 Upravljane znanjem - Knowledge Management Zasnovanost na znanju i organizaciono učenje Implementacija sistema upravljanja znanjem - knowledge management systems (KMS)
21 Literatura: Lieboviwitz J., R.W. Deutsch (Eds.) Knowledge Management Handbook, London: CRC Maier R. (2002) Knowledge Management Systems, Information and Communication Technologies for Knowledge Management, Berlin: Springer- Verlag Firestone, J., McElroy, M. (2004) Viewpoint: Organizational Learning and Knowledge Management: the Relationship, The Learning Organization, Vol. 11, No. 2, Firestone J. M., McElroy M. W. (2005) Doing Knowledge Management, The Learning Organization, 12, no.2 (April, 2005) McElroy M. W. (1999) The Second Generation of Knowledge Management, Management Knowledge (October,1999) Malhotra, Y. (2005) Integrating knowledge management technologies in organizational business processes: getting real time enterprises to deliver real business performance, Journal Of Knowledge Management Vol. 9 No. 1, Turban, E., J.E. Aronson, Ting-Peng Liang, (2005) Decision Support Systems and Intelligent Systems, Pearson Prentice Hall Heising,P., Vorbeck, J.:Knowledge management Concepts and best Practices Jetter, A.,Kraaijenbrink, J., Schroder, H., Wijnhoven, F.: Knowledge integration, Physica-Verlag,2006.
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