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DTSTAMP:20260511T183213Z
DESCRIPTION:Click for Latest Location Information: http://dgiq2022east.data
 versity.net/sessionPop.cfm?confid=151&proposalid=13891\n\nSo, you read the 
 book on Data Governance and attended many instructive sessions at DGIQ on D
 ata Quality. You understand the importance of an Enterprise Data Glossary a
 nd you know the difference between Master and Reference Data...Thus, you ha
 ve been appointed to supervise the “Data Management” portion of
  the new project to replace the core systems in your organization. Where to
  start? How should you do it? What tool do you need?\n\nThis session is bas
 ed on a real-life project at Université du Québec à Mo
 ntréal (UQAM) where the speaker is responsible for data management. 
 This is the first project of a large program to rewrite all applications ma
 naging students and academic activities. Its goal is to manage the programs
 , activities, and curriculum offered by UQAM. This is the “product MD
 M” of the university.\n\nAs part of his work, the speaker created a b
 usiness terms glossary, documented data quality rules in a repository, cons
 tructed data models, and, with the help of the team, developed data quality
  validation scripts to be included in the final product for ongoing DQ moni
 toring. All of this with simple, out-of-the-shelf tools.\n\nIn this session
 , you will see:\n\n\n	\n	An introduction to the project context\n	\n	\n
 How to move from the university’s by-laws to a glossary, to data qual
 ity rules, then to data models\n	\n	\n
 Why embedding data quality validation scripts as a development helping tool
 \n	\n	\n	What we will do better next time\n	\n\n
DTSTART:20221206T134500
SUMMARY:Implementing Data Quality Monitoring During Application Development
DTEND:20221206T142959
LOCATION: See Description
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