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TDWI Chicago Update

At TDWI, we have been working hard to navigate this ever-changing landscape in the face of COVID-19, and we want to assure you that the health and well-being of our employees, customers, and vendor partners is our top priority. Therefore, due to the growing concern around the coronavirus (COVID-19), and in alignment with the guidelines laid out by the CDC and WHO, we have decided to merge this year’s TDWI Chicago Conference (May 10-15) with TDWI Orlando 2020 (November 8-13), where it can be a successful experience for everyone. The Chicago 2020 agenda will be replicated at TDWI Orlando 2020.

Our registration team will be in contact with individual registrants and sponsors directly.

Course Description

Platforms & Architecture, Onsite, TDWI Foundations

M4A TDWI Data Virtualization: Solving Complex Data Integration Challenges

May 11, 2020

9:00 am - 12:15 pm

Duration: Half Day Course

Level: Beginner to Intermediate

Prerequisite: None

John L Myers

Research Analyst

Blue Buffalo Group

Preview Course Materials Course Outline

The data integration landscape has changed radically the past few years. What was once a relatively manageable problem of blending and unifying data from enterprise transaction systems has grown to encompass external data, Web data, clickstream data, end-user data, big data, cloud data, and more. New expectations for information-driven business agility further compound the complexities of modern data integration. The ETL-based data warehouse is no longer enough. Data virtualization is a core component of next-generation data integration architectures, techniques, and technology.

Get ready to expand your data integration capabilities, deliver business-speed information, and make the most of recent advances in data integration technology. Through a combination of lecture, exercises, and case study review you will learn how data virtualization works and how to position it in your data integration architecture and processes.

You Will Learn

  • Data virtualization definitions and terminology
  • Business case and technical rationale for data virtualization
  • Key concepts and foundational principles of virtualization--views, services, etc.
  • Data virtualization lifecycle, capabilities, and processes
  • How to extend the data warehouse with virtualization
  • How virtualization enables federation and enterprise data integration
  • How virtualization is applied for big data and cloud data challenges
  • How companies use virtualization to solve business problems and drive business agility

Geared To

  • BI, MDM, and data warehousing program and project managers
  • Data integration architects, designers, and developers
  • Data and technology architects