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DTSTAMP:20260519T182415Z
DESCRIPTION:Click for Latest Location Information: http://edw2020chicago.da
 taversity.net/sessionPop.cfm?confid=143&proposalid=12428\nPolyglot persiste
 nce lets enterprises store different kinds of data in different data stores
 , depending on how data is being used. The trend complements the evolu
 tion towards microservices, and introduces a whole range of new questions a
 bout consistency of the data and consistency of the data structure. Th
 e same data is described over and over again, in different languages, diffe
 rent formats, and different data types. As a result, things get lost a
 nd out of sync, leading to data quality challenges.\nHaving a sin
 gle source of truth and lifecycle management for your schemas can
  be a real challenge at scale when applications keep evolving at rapid spee
 d. While logical data models have served us well in the relational wor
 ld, we've come to realize their limitations when it comes to big data h
 ierarchical structures and polymorphism.\nIn this session, we will look at 
 the available options to define structures, so they can be reused in a vari
 ety of different target databases, storage formats, and communication proto
 cols.\n
DTSTART:20201020T110500
SUMMARY:Polyglot Data Modeling
DTEND:20201020T115459
LOCATION: See Description
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