Data virtualization is an approach to data management in which all of an organization’s data—including both structured and unstructured data sets (e.g., social media posts, images, videos, rich media, and audio files)—is accessible via a centralized data layer interface or dashboard. Regardless of how it’s formatted or where it lives (e.g., a database, a CRM, or Dropbox), data virtualization enables organizations to retrieve, manipulate, and analyze all of their data at any time.
Here’s how it works: Data virtualization platforms leverage the metadata of each piece of data, no matter how or where it’s stored. This enables employees to make sense of all data, whether it lives on-premises in a data center or in a data lake or data warehouse in the cloud—without having to move or copy any files or worry about changing formats. The technology essentially bridges the gap between disparate data sources and types, shattering data silos and giving organizations a clear view of the totality of their data while eliminating duplicate files and documents. Since employees no longer have to hop from repository to repository looking for information, data virtualization delivers much faster access to data—which in turn helps organizations make better decisions in less time.
Due to the benefits data virtualization provides (more on that in a bit), it comes as no surprise that one recent study found that the global data virtualization market, which brought in $1.68 billion in 2017, will grow to $8.36 billion by 2026. What’s more, according to Gartner, 60 percent of organizations will invest in data virtualization tools by 2022.
When you start to understand just how beneficial data virtualization can be, these numbers start to make a lot of sense.