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DTSTAMP:20260711T110614Z
DESCRIPTION:Click for Latest Location Information: http://edw2022.dataversi
 ty.net/sessionPop.cfm?confid=129&proposalid=13453\nArchitecting virtual dat
 a lake to integrate the machine data collected from the customer locations 
 with the rest of the enterprise data and provide important information to f
 ield engineers to perform timely preventative maintenance ensuring high cus
 tomer satisfaction. The machine data comes in different formats and with hi
 gh volume that's needs a different infrastructure to store the data. Th
 e field service engineers perform installations, repairs, preventative main
 tenance around those machines exist in customer locations. The service data
  around machines are stored in the enterprise data landscape. To increase t
 he availability of the machines, predictive machine maintenance is much nee
 ded in the given competitive semiconductor market environment. The Data Sci
 ence team owns the technical capability of building machine learning models
  to enable predictive maintenance to ensure those machines are running at t
 he highest availability and productivity. This presentation provides o
 n how we help the data scientists to get the data from machine and ent
 erprise data on an integrated business data model.
DTSTART:20220323T120000
SUMMARY:Architecting a Virtual Data Lake for Data Science to Enable Predict
 ive Analytics
DTEND:20220323T125959
LOCATION: See Description
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