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DESCRIPTION:Click for Latest Location Information: http://edw2024.dataversi
 ty.net/sessionPop.cfm?confid=159&proposalid=15034\nVirtually every company 
 worldwide is either using or learning to use machine learning (ML) and larg
 e language models (LLMs) to improve productivity and address scalability ch
 allenges. Robotic process automation, ML, and LLMs will dramatically change
  the way people work. Yet, the tools lack transparency and make it difficul
 t to understand what information was used to formulate answers, including t
 he timeliness, reliability, IP encumbrances, and other characteristics of t
 he data.\n\nThe most effective approach to providing metadata support to ad
 dress these challenges is through well-designed ontologies and knowledge gr
 aphs as key components of the underlying data fabric. The ontologies provid
 e structure for and across data sets, enable federated query support, and f
 acilitate data quality, provenance, and other analyses. Yet, ontologies can
  be expensive to build, and require collaboration across teams inside and a
 cross organizations. The EDM Council has developed an environment and repea
 table methodology to address many of the challenges in building high-qualit
 y, long-lived ontologies and knowledge graphs to support AI and other initi
 atives. The tools, developed over the last eight years, are open source and
  have been extended recently to support increasing levels of quality contro
 l, regression testing, data transformation, and continuous integration and 
 deployment (CI/CD). Our Data Innovation Laboratory (DIL) provides hosting a
 nd process templates that have been key to the success of a number of colla
 borative industry projects in finance, pharma, and manufacturing.\n\nIn thi
 s talk, we will:\n\n	describe the methodology\n
 provide an overview of the infrastructure\n
 discuss lessons learned in developing the tools we’ve built\n\nWe wil
 l also share how you can get involved and leverage the infrastructure in yo
 ur own quest to use ML, LLMs, and other emerging technologies.\n
DTSTART:20240326T134500
SUMMARY:A Collaborative Environment and Repeatable Process for Successful K
 nowledge Graph Development
DTEND:20240326T142959
LOCATION: See Description
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