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.
Data Virtualization Module 1. Data Virtualization Concepts and Principles
Data Virtualization Basics
Why Data Virtualization?
The Data Virtualization Foundation
Virtualize or Materialize?
Module 2. Data Integration Architecture
Integration Architecture Concepts
Reference Architectures
Integration Architecture Examples
Virtualize or Materialize?
Module 3. Data Virtualization in Integration Architecture
Virtualization in Data Integration Projects
Data Warehousing Use Cases
Data Federation Use Cases
MDM and EIM Use Cases
More Data Virtualization Applications
Virtualize or Materialize?
Module 4. Data Virtualization Platforms
Platform Requirements
Platform Capabilities
Platform Variations
Module 5. Implementing Data Virtualization
Analysis
Design and Modeling
Development
Deployment
Operation
Virtualize or Materialize?
Module 6. Getting Started with Data Virtualization
Skills and Competencies
Human Factors
Goals and Expectations
Best Practices
Join our public courses in our Russia facilities. Private class trainings will be organized at the location of your preference, according to your schedule.