Data virtualization is an emerging technology for data integration that is becoming more popular as organizations strive to improve data management and business agility. Data virtualization allows organizations to access and combine data from disparate data sources without having to physically consolidate the data. This can be a huge time and cost savings for organizations. Keep reading for a working data virtualization definition as well as information about its key features and benefits.
Data Virtualization in a Nutshell
Data virtualization is a technology that allows organizations to aggregate data from multiple, disparate data sources into a single logical view. The technology separates the process of data acquisition from the process of data consumption, which enables users to interact with the data as if it were all in one place. Data virtualization also eliminates the need to extract, transform and load tools and processes, since it can pull the necessary information directly from the source systems. This makes data integration easier and faster and helps to ensure the accuracy and consistency of information across different systems.
Key Features of Data Virtualization Technology
Data virtualization technology is a process that allows data to be accessed and used by business applications without having to be physically moved. This is done by creating a virtual view of the data that is composed of information from multiple data sources. The key features of data virtualization technology include:
- The ability to consolidate disparate data into a single source, making it easier for users to access and analyze the information
- The ability to improve performance by caching frequently used data locally
- The ability to mask the complexity of the underlying data sources, so that users only see what they need to see
- The ability to improve security by controlling access to the underlying data sources
The Benefits of Data Virtualization
Data virtualization is a process that allows multiple data sources to be accessed and used as if they were one source. This is done by creating a layer of data that sits between the user and the data sources. The benefits of data virtualization include improved performance, simplified management, and increased security.
Improved performance is a key benefit of data virtualization. By consolidating multiple data sources into one, the amount of time it takes to access the information is reduced. This is because there is no need to send requests to multiple locations; the information can be accessed from a single point. Additionally, since all of the data resides in one location, it can be cached which further improves performance.
Simplified management is another benefit of data virtualization. Since all of the data resides in one location, there is no need to manage multiple copies of the same information. In addition, administrators only need to understand how to use one tool rather than several tools from different vendors.
Increased security is yet another benefit of data virtualization. Data fragmentation can lead to exposure of sensitive information due to its spread out over multiple systems. By consolidating all of the data into one location, this risk is eliminated. Additionally, auditing and tracking capabilities are improved because all activity occurs on a single platform.
Getting Started with Data Virtualization
To get started with data virtualization, you first need to identify the sources of your data. Once you know where your data is coming from, you can begin assembling it into a virtualized dataset. This process generally involves creating a schema that defines how the data will be organized and accessed. You then use this schema to create one or more self-contained datasets that can be used for reporting and tracking purposes.
Simply put, data virtualization is a process that allows organizations to aggregate data from multiple data sources into a centralized location. This process allows for the data to be accessed and used in a more efficient and effective manner. Data virtualization can be used to improve data quality, make data more accessible, and improve decision-making. Overall, data virtualization can be a valuable tool for organizations.