Data Virtualization – Definition & Overview

What is data virtualization?

Data virtualization is an innovative approach in the field of data management. It serves as a virtual layer that allows for seamless data retrieval and manipulation, without delving into the technical complexities of the data. This entry aims to offer a comprehensive understanding of Data Virtualization, its core principles, and its applications in today’s data-centric world.

Data virtualization is a data management strategy that:

  • Abstracts Data: It provides a virtual layer that abstracts the underlying data sources.
  • Simplifies Access: Allows applications to easily retrieve and manipulate data.
  • Eliminates Complexity: Removes the need for understanding the technical details of the data.

Why is data virtualization important?

The importance of Data virtualization lies in its ability to:

  • Streamline Operations: It simplifies data management tasks, making it easier for businesses to focus on analytics and decision-making.
  • Enhance Flexibility: Offers the ability to work with data in real-time, without affecting the underlying data sources.
  • Improve Efficiency: Reduces the time and resources required to access data, especially in complex environments like cloud-based data warehouses.

Data virtualization in complex environments

Data virtualization is particularly useful in complex data environments such as Cloud-based Data Warehouses. It serves as a bridge that facilitates easier data access and manipulation, thereby enhancing the efficiency and effectiveness of cloud-based data solutions.