BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//hacksw/handcal//NONSGML v1.0//EN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260610T215144Z
DESCRIPTION:Click for Latest Location Information: http://edw2023digital.da
 taversity.net/sessionPop.cfm?confid=155&proposalid=14170\nOver the past few
  decades, Data Architecture has focused almost exclusively on managing data
  for analytics, with operational data viewed as “data sources.”
  Operational data is much more than source data for analytics. It is the da
 ta used to run the business, whereas analytical data is used to observe the
  business. Business operations don’t work without operational data, y
 et we’ve largely ignored it as a critical part of Data Management arc
 hitecture.\n\nOver the decades that we’ve disregarded operational dat
 a, many changes have occurred in the world of operational systems and data.
  What was once primarily transactional systems has evolved to encompass tra
 nsactions, workflow automation, process automation, commercial IoT, and ind
 ustrial IoT. Today’s transactional systems are dominated by purchased
  products, each with unique semantics, data models, and proprietary data ar
 chitecture. The result is a large accumulation of technical debt that limit
 s data exchange, data sharing, data interfaces, Data Quality, and even data
  meaning.\nIt is time to step up to operational data architecture – t
 o reduce technical debt and to prepare for changes yet to come. Concepts, t
 echniques, and technologies exist to meet operational data challenges. But 
 a fragmented, technology-first approach is time-consuming, costly, and ofte
 n chaotic. Well-designed operational data architecture organizes the techni
 ques and technologies to prevent chaos and improve data management.\n\nYou 
 will learn:\n\n	The variety of operational systems and the roles of each\n
 The variety of data created and managed by operational systems\n
 The implications of global data variations and mobile data variations\n
 The roles of MDM and RDM in operational Data Management\n
 The challenges of data sprawl, data disparity, and Data Management technica
 l debt\n
 Architectural concepts, constructs, and techniques to manage sprawl, dispar
 ity, and debt\n
 Design techniques for adaptable and sustainable architecture\n\n
DTSTART:20230327T080000
SUMMARY:T3: Operational Data Architecture
DTEND:20230327T105959
LOCATION: See Description
END:VEVENT
END:VCALENDAR