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DTSTAMP:20260421T221338Z
DESCRIPTION:Click for Latest Location Information: http://dgiq2024west.data
 versity.net/sessionPop.cfm?confid=160&proposalid=15294\nThe energy industry
  has experienced a rapid increase in measured and interpreted data creating
  challenges to data quality management, such as device calibration, interpr
 etation reliability, and data integration. Additionally, demand for high-qu
 ality data has intensified due to new large-scale uses in analytics, busine
 ss intelligence, data science, and machine learning. However, limited resou
 rces make it hard to address these challenges effectively.\n\nThis session 
 proposes a collaborative mechanism to prioritize data problems based on use
 rs' perspectives. The approach follows a double diamond divergence/conv
 ergence framework, with data users collaborating to identify and prioritize
  data types and their associated issues. The selected high-impact problems 
 are refined using the 5h2w technique, leading to an action plan for data qu
 ality improvement.\n\nThis innovative approach combines data management wit
 h design thinking, representing a pioneering endeavor in the energy industr
 y. The mechanism has already been successfully implemented yielding positiv
 e outcomes and earning recognition from the management team.\n\n	Planning\n
 Data mapping\n	Problem description\n	Action planning\n\n
DTSTART:20240603T170000
SUMMARY:Design Thinking Applied to Address Data Quality Issues
DTEND:20240603T174459
LOCATION: See Description
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