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DESCRIPTION:Click for Latest Location Information: http://edw2024.dataversi
 ty.net/sessionPop.cfm?confid=159&proposalid=15041\nData integration has bee
 n the primary method of resolving data disparity for decades. However, inte
 gration brings challenges with multiple copies of data and many data pipeli
 nes. Data interoperability is quickly becoming a preferred alternative to i
 ntegration. Interoperability eliminates the proliferation of data copies an
 d reduces the number and complexity of ETL processes and data pipelines. In
 teroperability also supports agility and adaptability. Data is not force-fi
 tted into a rigid schema but instead positioned as independent components t
 hat can be configured to fit many different use cases. \n\nMaking data
  interoperable begins with data architecture to identify interoperability p
 atterns and weave them into your existing data management architecture. Kno
 wing what patterns you'll use, APIs, data products, data contracts, sem
 antic mapping, open links, etc., is an essential first step. Next, you'
 ll need to identify the technologies needed to enable each pattern and fit 
 them into your technology stack. With those pieces in place, you're rea
 dy to provide design guidelines and begin migration planning.\n\nIn this tu
 torial you will learn:\n\n
 What is data interoperability and why is it important\n
 Adapting existing data management architecture to support interoperability\
 n	Interoperability patterns using data products, data contracts, and APIs\n
 Interoperability patterns based on semantic modeling and mapping\n
 Interoperability patterns with open links, data collaboration, and data vir
 tualization\n\n
DTSTART:20240325T124500
SUMMARY:T10: Architecture and Design for Data Interoperability
DTEND:20240325T155959
LOCATION: See Description
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