Overcoming Terminology Mismatches with Agile Data Governance and Warehousing
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  Geoffrey Malafsky   Geoffrey P Malafsky
Phasic Systems Inc


Tuesday, May 1, 2012
02:40 PM - 03:10 PM

Level:  Business / Non-Technical

Corporate data systems are plagued by redundant and low-quality data preventing effective data governance, data consolidation, Master Data Management, and data standardization. The most common hurdle to successful data governance is the inability to determine the true meaning of data elements in a business context so standardized definitions and business rules can be created and used across applications, data systems, and business groups. Agility is required to match design and development time with accurate, common, consistent data on the timescale of business decisions and operations.

Business context cannot be determined solely from technical metadata since actual data meaning (its semantics) frequently differs from table and element titles, and varies across data systems and applications. Standard data modeling techniques are too rigid, slow, and incapable of handling important semantic variations since they require well-defined common concepts which is a major hurdle as even simple terms like 'customer', 'account', and 'client' have multiple important business meanings that cannot be distilled into single universal definition. Agile governance and warehousing can be achieved by rapidly identifying core and extended definitions in their business context, and representing them in an actionable architecture. A Unified Business Model built on a standards based canonical model enables re-adding business context to data to produce visible, and collaborative common definitions, data models, codes, and glossaries that both embraces semantic variation and significantly accelerates model design, data system implementation, and unified data integration.

Dr. Geoffrey Malafsky has a PhD in Nanotechnology from The Pennsylvania State University. He was a research scientist at the Naval Research Laboratory before becoming a technology consultant in advanced system capabilities and designs for numerous Government agencies. He has over 25 years of experience and is an expert in multiple fields ranging from Nanotechnology, modeling & simulation, Knowledge Discovery & Dissemination, object-attribute data systems, and information engineering. He founded and operated the technology consulting company TECHi2 providing support for challenging problems in enterprise-scale data engineering, Knowledge Management, Enterprise Architecture, Business Intelligence, and rapid prototyping of distributed web systems. He is now CEO of software start-up company Phasic Systems Inc offering the DataStar product suite with its innovations in semantic technology, object-based data models, and high-performance web data transactions to the Government and corporate markets for enterprise-scale high-quality authoritative data.

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