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DTSTAMP:20260420T131530Z
DESCRIPTION:Click for Latest Location Information: http://edw2019.dataversi
 ty.net/sessionPop.cfm?confid=126&proposalid=10515\n<p>NOTE: This seminar is
  continued from Thursday afternoon.</p>\n<p>A deliberate architecture for d
 ata integration helps keep projects on schedule and on budget; improves dat
 a quality and data governance; and increases business users&rsquo; confiden
 ce in data. But many companies resort to a trial-and-error method of gather
 ing data that is disorganized and incomplete. In this workshop, you&rsquo;l
 l learn how to design a hybrid integration architecture that supports data,
  application, and cloud integration. Data may be stored in relational, colu
 mnar, or in-memory DBMS, NoSQL, or Hadoop; logical DW, data lake, or data h
 ub; data virtualization; data services, both inter- and intra-enterprise; a
 nd, within analytical processes (data blending or preparation). We will rev
 iew and contrast integration use cases and best practices spanning technolo
 gies. We will review roles&nbsp;and responsibilities of IT, data science te
 ams, &ldquo;citizen&rdquo; data scientists, and business &ldquo;power&rdquo
 ; users.</p>\n<p>Key topics:</p>\n\n
 Underlying concepts and architectures\n
 Use cases and best fit technologies\n	Best and pragmatic practices\n
 Roles and responsibilities of integrators\n\n<p>Many enterprises have siloe
 d integration efforts that are redundant and overlapping. This tutorial wil
 l discuss, contrast, and match various types of integration use cases, arch
 itectures, technologies, and products.</p>\n
DTSTART:20190322T083000
SUMMARY:Designing a Deliberate Architecture for Data Engineering, Data Inte
 gration, Application Integration, and Data Preparation
DTEND:20190322T114459
LOCATION: See Description
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