The critical component of data virtualization for enterprises
- Data virtualization integrates data from multiple sources, locations, and formats to create a single stream of data without any overlap or redundancy
- Virtualized data allows the folks in sales, marketing, IT, and operations to get answers that span multiple data stores
- The global data virtualization cloud market is forecasted to expand at a stellar growth of 25%, and surpass a valuation of US$5.6 billion by 2030
In the current era of high-speed information and constant data transmission, new techniques to assist in combining, gathering, and curating a great amount of data is increasingly vital. Among them is data virtualization, which refers to the collections and integration of information from different locations, sources, and formats, to develop a single, trustable source of data without any redundancy or overlap.
Given how IT companies have multiple collection points of information, gathering data can be arduous and time-consuming. Thus, data virtualization software can help them have faster and better integration tools that can inform their decision-making process. According to a 2020 market study by Future Market Insights (FMI), the global data virtualization cloud market is forecasted to witness substantial growth in terms of value between 2020 and 2030.
The report attributes the growth of the market to the growing shift towards an awareness of business resilience, cost optimization, and Infrastructure-as-a-Service (IaaS) within the IT sector, which in turn, is propelling the adoption of data virtualization cloud. Moreover, shifting preference from local servers to cloud systems for easier data management is expected to fuel the growth of the market.
FMI also predicts that the global data virtualization cloud market is forecasted to expand at a stellar growth of 25% and surpass a valuation of US$5.6 billion by 2030. Zooming into the regional landscape, North America will continue to lead other territories, backed by the presence of established market leaders and an advanced IT infrastructure in the region.
What is data virtualization?
In a nutshell, data virtualization creates one “virtual” layer of data that distributes unified data services across multiple users and applications. This gives users quick access to all data, cuts down on data replication, reduces costs, and provides data flexibility to change business decisions. Though it performs like traditional data integration, data virtualization uses modern tech to bring real-time data integration together for less money, and more flexibility.
It has the ability to replace current forms of data integration and lessens the need for replicated data marts and data warehouses. Data virtualization can seamlessly function between derived data resources and original data sources, whether from an onsite server farm or a cloud-based storage facility. This allows businesses to bring their data together quickly and cleanly.
How virtualization works and why enterprises need it
To understand how data virtualization works, envision a database that has entries from Software as a service (SaaS) applications, enterprise data warehouses, emails, and business applications. Information about formatting, sources, and application location makes this data harder to manipulate, store, and secure.
When data is virtualized, only the metadata (or top-level data) is used. Businesses can access data repositories regardless of the location or platform on which they reside to conduct joins between different fact tables, allowing users to assemble richer pictures from which to draw insights.
A single “virtual” data layer provides faster access to data, with nearly zero lag, significantly less lead time for designing and implementation for data availability, less data redundancy, and more agility to change. That said, without advancing data virtualization first, there will be no progress in making the hybrid cloud more agile or accessible.
Basically, virtualized data allows the folks in sales, marketing, IT, and operations to get answers that span multiple datastores. Without virtualized data, the hybrid cloud would be a slow, insecure, unresponsive, and expensive collection of data without the ability to answer the high-value questions every enterprise has.