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Data Engineering Design Patterns
Data Virtualization - Integrating Data from Disparate Sources

Data Virtualization: Integrating Data from Disparate Sources

Introduction

In the modern data landscape, organizations often find themselves dealing with a multitude of data sources, each with its own unique structure, format, and access mechanisms. This fragmentation of data can make it challenging to gain a comprehensive and unified view of the organization's information assets. Data virtualization emerges as a powerful solution to this problem, enabling the integration of data from disparate sources into a seamless, abstracted layer that provides users with a centralized and consistent view of the data.

Data Virtualization Design Pattern

Data virtualization is a design pattern that allows for the creation of a virtual data layer that sits between the data sources and the consumers of that data. This virtual layer acts as an intermediary, abstracting the underlying complexities of the data sources and presenting a unified, standardized view of the data to the end-users or applications.

The key components of the data virtualization design pattern are:

  1. Data Sources: These are the various databases, data warehouses, data lakes, and other data repositories that contain the organization's data.
  2. Data Virtualization Layer: This is the abstraction layer that integrates and harmonizes the data from the disparate sources, providing a consistent and standardized view of the data.
  3. Data Consumers: These are the users, applications, or downstream systems that access and utilize the data made available through the data virtualization layer.

![Data Virtualization Design Pattern](https://www.plantuml.com/plantuml/png/ZPB1Rjim4CVtynHLjVL2Aq4Aq8Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0Wg4Iq0 (opens in a new tab)

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