What is Data Virtualization? How to Approach It?

Acing the digital landscape is a continuous ambition for global enterprises. However, only those who follow a data-centric approach get closer to it while the rest are left entangled in the mess. Enterprise data management provides a distinctive edge and sharpens the enterprise’s ability to foresee trends and virtualization is an integral part of the stack here. For CIOs and other data security leaders, virtualization is an important step to protect the most important source systems from data modification whether intentional or unintentional.

To put it simply, data virtualization is a logical data layer that combines disparate systems and unifies the data stream for centralized governance.

Now, data virtualization is a key practice as it provides full-fledged data discovery, transportation and search system. Over the years, enterprises have woken up to building a parallel practice out of it. As far as the market demand is concerned, the virtualization market size is expected to touch USD 4.12 Billion by 2022 at a CAGR of 21.1%.

With virtualization, an organization can make data sets accessible to more users with ease than before. That is why all Enterprise Data Management (EDM) initiatives are being steadily acknowledged under Enterprise Data Virtualization (EDV).

  • Virtualization provides a starting point to all the enterprises aiming for the modernization of their infrastructure. It makes it easier to adopt contemporary cloud solutions without leaving any major impact on the ongoing processes. Through abstracting underlying systems, moving on from legacy systems gets achievable.
  • It eliminates the cost and effort that goes into data replication in traditional processes. Such a ‘zero-replication’ approach, assures in-the-moment information access without having to splurge extra investments.
  • Given the ability to provide on-demand access to the most current data of business entities, virtualization enhances productivity at the individual level.
  • Since the dependency on the manual effort goes down, virtualization lets CIOs cut down on development resources and deploy a smarter and leaner team.

However, lack of planning can produce unforeseen challenges in data throughout, quality and performance. Given the proliferation of real-time data across enterprises, on-demand visibility into data architecture and governance should be unmissable. If not, this affects validation processes thereby consuming additional time in resolving discrepancies.

To address these issues, organizations need a smarter low-code approach that also delivers lightning speed at the same time. For example, K2view’s Data Fabric provides an integral low-code template for creating, debugging and executing web services for actionable use-cases.

Accessing data from a wide range of source systems, structures and formats is a cumbersome process. With a dynamic approach to virtualization, the fabric addresses this issue. It uses a logical abstraction layer that holds the field’s schema of a business entity. They manage hundreds of these multiple digital entities.

Likewise, enterprises can embrace dynamic virtualization to achieve unbeatable speed, efficiency from the source systems to target apps.

The Roadmap You Need

  • Educate all stakeholders about virtualization. All business users deserve to learn about the benefits of expanding virtualization to other areas.
  • Emphasize parallel processing to manage queries on high-volume data. This can be assured with performance tuning and aggressive QA analysis of scalability. Remember, there’s a lot of unpredictability with ad-hoc analysis. More the testing, better the virtualization framework.
  • Break down the data virtualization implementation into phases. Start with abstracting all the data sources and then demarcate the data sets into layers.

Take a hybrid approach Virtualize or store

Data Virtualization provides a choice to either virtualize all the data of a digital entity or selectively store few data sets physically on a micro-DB. While the lifecycle of virtualization (unified, transformed, orchestrated and transported from source to target for the selected sets is intact, storing has the following benefits:

  • Store a digital entity’s data that does not change frequently. This lessens the burden on source physical systems.
  • Add new fields to the entity data that otherwise do not exist in the source system.


While you prepare to explore and implement a virtualization practice, it is equally important to convey your vision to all users and developers. Prepare user guides and make it a regular practice to educate them about the new-age EDM practice. While the global companies plan to survive the hyper-digital space, virtualization should top the COE stack.