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DTSTAMP:20260420T124332Z
DESCRIPTION:Click for Latest Location Information: http://edw2019.dataversi
 ty.net/sessionPop.cfm?confid=126&proposalid=10367\n<p>Modern BI and analyti
 cal architecture has evolved beyond traditional DW with elements such as a 
 logical data warehouse, data lakes, distribution hub, data catalog, analyti
 cal sandbox, and data science hub, along with both self-service data prepar
 ation and BI. But achieving an ROI with these approaches is fruitless witho
 ut the right data and technical architectures. This workshop clarifies what
  you need to know regarding structured, unstructured and semi-structured da
 ta; hybrid integration and data engineering; and analytical uses by casual 
 info consumers, power users and data scientists. Technologies include datab
 ases (relational, columnar, in-memory, Hadoop and NoSQL); hybrid data, appl
 ication and cloud integration; data preparation; data virtualization; descr
 iptive, diagnostic, predictive, and prescriptive analytics; and on-premise,
  cloud or hybrid deployments.</p>\n<p>Architecture includes:</p>\n\n
 Data structures and workflow\n
 Data engineering, data integration, data preparation and data virtualizatio
 n\n	Business intelligence and advanced analytics\n	Enabling technologies\n
 Enterprise information management and data governance\n\n
DTSTART:20190318T083000
SUMMARY:Designing a Data Architecture for Modern Business Intelligence and 
 Analytics
DTEND:20190318T114459
LOCATION: See Description
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