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Što utječe na kvalitetu podataka i kako je unaprijediti koristeći Data Quality framework
Ako provedete više vremena nad ispravkama nego na razvoju sustava, shvatite da je to greška i da je vrijeme za promjene! Teorijske inicijative i standardizacija zahtijevaju kompleksnu implementaciju i ponekad odlučimo to ignorirati. Loša kvaliteta podataka, nejasni poslovni zahtjevi i k tome još poneka greška u fazi razvoja, na jednom su nas projektu dovele do situacije koja je tražila preuzimanje inicijative i drugačije rješavanje problema. U vrlo kratkom periodu ta inicijativa je uzrokovala preokret u izgradnji DWH/BI sustava. Izradom frameworka i produkta riješili smo mnoge probleme i osigurali da isporuke budu točnije, kvalitetni podaci budu proslijeđeni korisnicima, dok su nekvalitetni podaci bili prepoznati i nakon toga ispravljeni. Kroz predavanje prikazat ćemo inovativni pristup rješavanju projektnih problema s kojima smo se susreli, a upoznati ćemo i načine osiguranja kvalitete podataka s kojima smo uspješno izveli dosadašnje Data Warehouse projekte.
Ovo predavanje pokazati će kako na jednostavan način možemo uspostaviti proces upravljanja kvalitetom podataka a istovremeno imati proces koji se može nadograđivati iterativno. Također, biti će prikazana praktična iskustva i demonstracija procesa. 

Gartner positions IBM platform as a leader in two "Magic Quadrants for master data management" - management of customer information and products. The presentation will show the most important functionality of the platform and several case studies of implementation in complex environments.

Data Govrenance is a diverse set of activities: from defining the responsibilities of the data through the establishment of internal standards of quality, to arbitration in cases of data sharing. The main goal of Data Governance is to reduce the possibility of occurrence of adverse events in business resulting from poor quality data. Master Data Management is one of the key elements of the concept. The lecture gives an overview of common steps in the development of Data Governance in the company, and guidelines for the introduction of Data Gorvernance concepts. Certain elements of this process will be supported by examples from the Croatian practice.

Master data is the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise including customers, prospects, suppliers, sites, hierarchies, chart of accounts and many more industry specific entities. Master data management (MDM) is a discipline in which business and IT work together to ensure the uniformity, accuracy, semantic consistency and accountability of the enterprise’s official shared master data assets. Prerequisite for successful master data management implementation is enterprises’ awareness and acknowledgement of data as a crucial business asset. This lecture gives an introduction to master data management flavors, overview of benefits gained by its implementation and current MDM market overview.